The Rosenberg Self-Esteem Scale and Harter's Self-Perception Profile for Adolescents: A Concurrent Validity Study.

ERIC Educational Resources Information Center

Hagborg, Winston J.

1993-01-01

Administered Rosenberg Self-Esteem Scale (RSE) and Harter's Self-Perception Profile for Adolescents to 150 adolescents in grades 8 through 12. Correlational and cross-validation multiple regression analyses found that RSE total score and both its factor scores were strongly related to Global Self-Worth. Females reported significantly lower RSE…

Examination of the Relation between the Values of Adolescents and Virtual Sensitiveness

ERIC Educational Resources Information Center

Yilmaz, Hasan

2013-01-01

The aim of this study is to examine the relation between the values adolescents have and virtual sensitiveness. The study is carried out on 447 adolescents, 160 of whom are female, 287 males. The Humanistic Values Scale and Virtual Sensitiveness scale were used. Pearson Product Moment Coefficient and multiple regression analysis techniques were…

Loneliness among University Students: Predictive Power of Sex Roles and Attachment Styles on Loneliness

ERIC Educational Resources Information Center

Ilhan, Tahsin

2012-01-01

This study examined the predictive power of sex roles and attachment styles on loneliness. A total of 188 undergraduate students (114 female, and 74 male) from Gazi University completed the Bem Sex Role Inventory, UCLA Loneliness Scale, and Relationship Scales Questionnaire. Hierarchic Multiple Regression analysis and t-test were used to test…

Applications for predicting precipitation and vegetation patterns at landscape scale using lightning strike data

Treesearch

Deborah Ulinski Potter

1999-01-01

Previous publications discussed the results of my dissertation research on relationships between seasonality in precipitation and vegetation patterns at landscape scale. Summer precipitation at a study site in the Zuni Mountains, NM, was predicted from lightning strike and relative humidity data using multiple regression. Summer precipitation patterns were mapped using...

Modeling brook trout presence and absence from landscape variables using four different analytical methods

USGS Publications Warehouse

Steen, Paul J.; Passino-Reader, Dora R.; Wiley, Michael J.

2006-01-01

As a part of the Great Lakes Regional Aquatic Gap Analysis Project, we evaluated methodologies for modeling associations between fish species and habitat characteristics at a landscape scale. To do this, we created brook trout Salvelinus fontinalis presence and absence models based on four different techniques: multiple linear regression, logistic regression, neural networks, and classification trees. The models were tested in two ways: by application to an independent validation database and cross-validation using the training data, and by visual comparison of statewide distribution maps with historically recorded occurrences from the Michigan Fish Atlas. Although differences in the accuracy of our models were slight, the logistic regression model predicted with the least error, followed by multiple regression, then classification trees, then the neural networks. These models will provide natural resource managers a way to identify habitats requiring protection for the conservation of fish species.

Depressive disorder in pregnant Latin women: does intimate partner violence matter?

PubMed

Fonseca-Machado, Mariana de Oliveira; Alves, Lisiane Camargo; Monteiro, Juliana Cristina Dos Santos; Stefanello, Juliana; Nakano, Ana Márcia Spanó; Haas, Vanderlei José; Gomes-Sponholz, Flávia

2015-05-01

To identify the association of antenatal depressive symptoms with intimate partner violence during the current pregnancy in Brazilian women. Intimate partner violence is an important risk factor for antenatal depression. To the authors' knowledge, there has been no study to date that assessed the association between intimate partner violence during pregnancy and antenatal depressive symptoms among Brazilian women. Cross-sectional study. Three hundred and fifty-eight pregnant women were enrolled in the study. The Edinburgh Postnatal Depression Scale and an adapted version of the instrument used in the World Health Organization Multi-country Study on Women's Health and Domestic Violence were used to measure antenatal depressive symptoms and psychological, physical and sexual acts of intimate partner violence during the current pregnancy respectively. Multiple logistic regression and multiple linear regression were used for data analysis. The prevalence of antenatal depressive symptoms, as determined by the cut-off score of 12 in the Edinburgh Postnatal Depression Scale, was 28·2% (101). Of the participants, 63 (17·6%) reported some type of intimate partner violence during pregnancy. Among them, 60 (95·2%) reported suffering psychological violence, 23 (36·5%) physical violence and one (1·6%) sexual violence. Multiple logistic regression and multiple linear regression indicated that antenatal depressive symptoms are extremely associated with intimate partner violence during pregnancy. Among Brazilian women, exposure to intimate partner violence during pregnancy increases the chances of experiencing antenatal depressive symptoms. Clinical nurses and nurses midwifes should pay attention to the particularities of Brazilian women, especially with regard to the occurrence of intimate partner violence, whose impacts on the mental health of this population are extremely significant, both during the gestational period and postpartum. © 2015 John Wiley & Sons Ltd.

Multiple regression and Artificial Neural Network for long-term rainfall forecasting using large scale climate modes

NASA Astrophysics Data System (ADS)

Mekanik, F.; Imteaz, M. A.; Gato-Trinidad, S.; Elmahdi, A.

2013-10-01

In this study, the application of Artificial Neural Networks (ANN) and Multiple regression analysis (MR) to forecast long-term seasonal spring rainfall in Victoria, Australia was investigated using lagged El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) as potential predictors. The use of dual (combined lagged ENSO-IOD) input sets for calibrating and validating ANN and MR Models is proposed to investigate the simultaneous effect of past values of these two major climate modes on long-term spring rainfall prediction. The MR models that did not violate the limits of statistical significance and multicollinearity were selected for future spring rainfall forecast. The ANN was developed in the form of multilayer perceptron using Levenberg-Marquardt algorithm. Both MR and ANN modelling were assessed statistically using mean square error (MSE), mean absolute error (MAE), Pearson correlation (r) and Willmott index of agreement (d). The developed MR and ANN models were tested on out-of-sample test sets; the MR models showed very poor generalisation ability for east Victoria with correlation coefficients of -0.99 to -0.90 compared to ANN with correlation coefficients of 0.42-0.93; ANN models also showed better generalisation ability for central and west Victoria with correlation coefficients of 0.68-0.85 and 0.58-0.97 respectively. The ability of multiple regression models to forecast out-of-sample sets is compatible with ANN for Daylesford in central Victoria and Kaniva in west Victoria (r = 0.92 and 0.67 respectively). The errors of the testing sets for ANN models are generally lower compared to multiple regression models. The statistical analysis suggest the potential of ANN over MR models for rainfall forecasting using large scale climate modes.

Downscaling Land Surface Temperature in Complex Regions by Using Multiple Scale Factors with Adaptive Thresholds

PubMed Central

Yang, Yingbao; Li, Xiaolong; Pan, Xin; Zhang, Yong; Cao, Chen

2017-01-01

Many downscaling algorithms have been proposed to address the issue of coarse-resolution land surface temperature (LST) derived from available satellite-borne sensors. However, few studies have focused on improving LST downscaling in urban areas with several mixed surface types. In this study, LST was downscaled by a multiple linear regression model between LST and multiple scale factors in mixed areas with three or four surface types. The correlation coefficients (CCs) between LST and the scale factors were used to assess the importance of the scale factors within a moving window. CC thresholds determined which factors participated in the fitting of the regression equation. The proposed downscaling approach, which involves an adaptive selection of the scale factors, was evaluated using the LST derived from four Landsat 8 thermal imageries of Nanjing City in different seasons. Results of the visual and quantitative analyses show that the proposed approach achieves relatively satisfactory downscaling results on 11 August, with coefficient of determination and root-mean-square error of 0.87 and 1.13 °C, respectively. Relative to other approaches, our approach shows the similar accuracy and the availability in all seasons. The best (worst) availability occurred in the region of vegetation (water). Thus, the approach is an efficient and reliable LST downscaling method. Future tasks include reliable LST downscaling in challenging regions and the application of our model in middle and low spatial resolutions. PMID:28368301

100-point scale evaluating job satisfaction and the results of the 12-item General Health Questionnaire in occupational workers.

PubMed

Kawada, Tomoyuki; Yamada, Natsuki

2012-01-01

Job satisfaction is an important factor in the occupational lives of workers. In this study, the relationship between one-dimensional scale of job satisfaction and psychological wellbeing was evaluated. A total of 1,742 workers (1,191 men and 551 women) participated. 100-point scale evaluating job satisfaction (0 [extremely dissatisfied] to 100 [extremely satisfied]) and the General Health Questionnaire, 12-item version (GHQ-12) evaluating psychological wellbeing were used. A multiple regression analysis was then used, controlling for gender and age. The change in the GHQ-12 and job satisfaction scores after a two-year interval was also evaluated. The mean age for the subjects was 42.2 years for the men and 36.2 years for the women. The GHQ-12 and job satisfaction scores were significantly correlated in each generation. The partial correlation coefficients between the changes in the two variables, controlling for age, were -0.395 for men and -0.435 for women (p< 0.001). A multiple regression analysis revealed that the 100-point job satisfaction score was associated with the GHQ-12 results (p< 0.001). The adjusted multiple correlation coefficient was 0.275. The 100-point scale, which is a simple and easy tool for evaluating job satisfaction, was significantly associated with psychological wellbeing as judged using the GHQ-12.

An open-access CMIP5 pattern library for temperature and precipitation: description and methodology

NASA Astrophysics Data System (ADS)

Lynch, Cary; Hartin, Corinne; Bond-Lamberty, Ben; Kravitz, Ben

2017-05-01

Pattern scaling is used to efficiently emulate general circulation models and explore uncertainty in climate projections under multiple forcing scenarios. Pattern scaling methods assume that local climate changes scale with a global mean temperature increase, allowing for spatial patterns to be generated for multiple models for any future emission scenario. For uncertainty quantification and probabilistic statistical analysis, a library of patterns with descriptive statistics for each file would be beneficial, but such a library does not presently exist. Of the possible techniques used to generate patterns, the two most prominent are the delta and least squares regression methods. We explore the differences and statistical significance between patterns generated by each method and assess performance of the generated patterns across methods and scenarios. Differences in patterns across seasons between methods and epochs were largest in high latitudes (60-90° N/S). Bias and mean errors between modeled and pattern-predicted output from the linear regression method were smaller than patterns generated by the delta method. Across scenarios, differences in the linear regression method patterns were more statistically significant, especially at high latitudes. We found that pattern generation methodologies were able to approximate the forced signal of change to within ≤ 0.5 °C, but the choice of pattern generation methodology for pattern scaling purposes should be informed by user goals and criteria. This paper describes our library of least squares regression patterns from all CMIP5 models for temperature and precipitation on an annual and sub-annual basis, along with the code used to generate these patterns. The dataset and netCDF data generation code are available at doi:10.5281/zenodo.495632.

Health-related quality of life in multiple sclerosis: role of cognitive appraisals of self, illness and treatment.

PubMed

Wilski, Maciej; Tasiemski, Tomasz

2016-07-01

Health-related quality of life (HRQoL) is considered an important measure of treatment and rehabilitation outcomes in multiple sclerosis (MS) patients. In this study, we used multivariate regression analysis to examine the role of cognitive appraisals, adjusted for clinical, socioeconomic and demographic variables, as correlates of HRQoL in MS. The cross-sectional study included 257 MS patients, who completed Multiple Sclerosis Impact Scale, Generalized Self-Efficacy Scale, Rosenberg Self-Esteem Scale, Brief Illness Perception Questionnaire, Treatment Beliefs Scale, Actually Received Support Scale (a part of Berlin Social Support Scale) and Socioeconomic Resources Scale. Demographic and clinical characteristics of the participants were collected with a self-report survey. Correlation and regression analyses were conducted to determine associations between the variables. Five variables, illness identity (β = 0.29, p ≤ 0.001), self-esteem (β = -0.22, p ≤ 0.001), general self-efficacy (β = -0.21, p ≤ 0.001), disability subgroup "EDSS" (β = 0.14, p = 0.006) and age (β = 0.12, p = 0.012), were significant correlates of HRQoL in MS. These variables explained 46 % of variance in the dependent variable. Moreover, we identified correlates of physical and psychological dimensions of HRQoL. Cognitive appraisals, such as general self-efficacy, self-esteem and illness perception, are more salient correlates of HRQoL than social support, socioeconomic resources and clinical characteristics, such as type and duration of MS. Therefore, interventions aimed at cognitive appraisals may also improve HRQoL of MS patients.

Factor Structure of the Primary Scales of the Inventory of Personality Organization in a Nonclinical Sample Using Exploratory Structural Equation Modeling

ERIC Educational Resources Information Center

Ellison, William D.; Levy, Kenneth N.

2012-01-01

Using exploratory structural equation modeling and multiple regression, we examined the factor structure and criterion relations of the primary scales of the Inventory of Personality Organization (IPO; Kernberg & Clarkin, 1995) in a nonclinical sample. Participants (N = 1,260) completed the IPO and measures of self-concept clarity, defenses,…

Spatial, spectral and temporal patterns of tropical forest cover change as observed with multiple scales of optical satellite data.

Treesearch

D.J. Hayes; W.B. Cohen

2006-01-01

This article describes the development of a methodology for scaling observations of changes in tropical forest cover to large areas at high temporal frequency from coarse-resolution satellite imagery. The approach for estimating proportional forest cover change as a continuous variable is based on a regression model that relates multispectral, multitemporal Moderate...

The impact of menopausal symptoms on work ability.

PubMed

Geukes, Marije; van Aalst, Mariëlle P; Nauta, Mary C E; Oosterhof, Henk

2012-03-01

Menopause is an important life event that may have a negative influence on quality of life. Work ability, a concept widely used in occupational health, can predict both future impairment and duration of sickness absence. The aim of this study was to examine the impact of menopausal symptoms on work ability. This was a cross-sectional study that used a sample of healthy working Dutch women aged 44 to 60 years. Work ability was measured using the Work Ability Index, and menopausal symptoms were measured using the Greene Climacteric Scale. Stepwise multiple linear regression models were used to examine the relationship between menopausal symptoms and work ability. A total of 208 women were included in this study. There was a significant negative correlation between total Greene Climacteric Scale score and Work Ability Index score. Total Greene Climacteric Scale score predicted 33.8% of the total variance in the Work Ability Index score. Only the psychological and somatic subscales of the Greene Climacteric Scale were significant predictors in multiple linear regression analysis. Together, they accounted for 36.5% of total variance in Work Ability Index score. Menopausal symptoms are negatively associated with work ability and may increase the risk of sickness absence.

Cooperation without culture? The null effect of generalized trust on intentional homicide: a cross-national panel analysis, 1995-2009.

PubMed

Robbins, Blaine

2013-01-01

Sociologists, political scientists, and economists all suggest that culture plays a pivotal role in the development of large-scale cooperation. In this study, I used generalized trust as a measure of culture to explore if and how culture impacts intentional homicide, my operationalization of cooperation. I compiled multiple cross-national data sets and used pooled time-series linear regression, single-equation instrumental-variables linear regression, and fixed- and random-effects estimation techniques on an unbalanced panel of 118 countries and 232 observations spread over a 15-year time period. Results suggest that culture and large-scale cooperation form a tenuous relationship, while economic factors such as development, inequality, and geopolitics appear to drive large-scale cooperation.

Introduction to the use of regression models in epidemiology.

PubMed

Bender, Ralf

2009-01-01

Regression modeling is one of the most important statistical techniques used in analytical epidemiology. By means of regression models the effect of one or several explanatory variables (e.g., exposures, subject characteristics, risk factors) on a response variable such as mortality or cancer can be investigated. From multiple regression models, adjusted effect estimates can be obtained that take the effect of potential confounders into account. Regression methods can be applied in all epidemiologic study designs so that they represent a universal tool for data analysis in epidemiology. Different kinds of regression models have been developed in dependence on the measurement scale of the response variable and the study design. The most important methods are linear regression for continuous outcomes, logistic regression for binary outcomes, Cox regression for time-to-event data, and Poisson regression for frequencies and rates. This chapter provides a nontechnical introduction to these regression models with illustrating examples from cancer research.

Automated Pathogenesis-Based Diagnosis of Lumbar Neural Foraminal Stenosis via Deep Multiscale Multitask Learning.

PubMed

Han, Zhongyi; Wei, Benzheng; Leung, Stephanie; Nachum, Ilanit Ben; Laidley, David; Li, Shuo

2018-02-15

Pathogenesis-based diagnosis is a key step to prevent and control lumbar neural foraminal stenosis (LNFS). It conducts both early diagnosis and comprehensive assessment by drawing crucial pathological links between pathogenic factors and LNFS. Automated pathogenesis-based diagnosis would simultaneously localize and grade multiple spinal organs (neural foramina, vertebrae, intervertebral discs) to diagnose LNFS and discover pathogenic factors. The automated way facilitates planning optimal therapeutic schedules and relieving clinicians from laborious workloads. However, no successful work has been achieved yet due to its extreme challenges since 1) multiple targets: each lumbar spine has at least 17 target organs, 2) multiple scales: each type of target organ has structural complexity and various scales across subjects, and 3) multiple tasks, i.e., simultaneous localization and diagnosis of all lumbar organs, are extremely difficult than individual tasks. To address these huge challenges, we propose a deep multiscale multitask learning network (DMML-Net) integrating a multiscale multi-output learning and a multitask regression learning into a fully convolutional network. 1) DMML-Net merges semantic representations to reinforce the salience of numerous target organs. 2) DMML-Net extends multiscale convolutional layers as multiple output layers to boost the scale-invariance for various organs. 3) DMML-Net joins a multitask regression module and a multitask loss module to prompt the mutual benefit between tasks. Extensive experimental results demonstrate that DMML-Net achieves high performance (0.845 mean average precision) on T1/T2-weighted MRI scans from 200 subjects. This endows our method an efficient tool for clinical LNFS diagnosis.

Estimating interaction on an additive scale between continuous determinants in a logistic regression model.

PubMed

Knol, Mirjam J; van der Tweel, Ingeborg; Grobbee, Diederick E; Numans, Mattijs E; Geerlings, Mirjam I

2007-10-01

To determine the presence of interaction in epidemiologic research, typically a product term is added to the regression model. In linear regression, the regression coefficient of the product term reflects interaction as departure from additivity. However, in logistic regression it refers to interaction as departure from multiplicativity. Rothman has argued that interaction estimated as departure from additivity better reflects biologic interaction. So far, literature on estimating interaction on an additive scale using logistic regression only focused on dichotomous determinants. The objective of the present study was to provide the methods to estimate interaction between continuous determinants and to illustrate these methods with a clinical example. and results From the existing literature we derived the formulas to quantify interaction as departure from additivity between one continuous and one dichotomous determinant and between two continuous determinants using logistic regression. Bootstrapping was used to calculate the corresponding confidence intervals. To illustrate the theory with an empirical example, data from the Utrecht Health Project were used, with age and body mass index as risk factors for elevated diastolic blood pressure. The methods and formulas presented in this article are intended to assist epidemiologists to calculate interaction on an additive scale between two variables on a certain outcome. The proposed methods are included in a spreadsheet which is freely available at: http://www.juliuscenter.nl/additive-interaction.xls.

BAYESIAN METHODS FOR REGIONAL-SCALE EUTROPHICATION MODELS. (R830887)

EPA Science Inventory

We demonstrate a Bayesian classification and regression tree (CART) approach to link multiple environmental stressors to biological responses and quantify uncertainty in model predictions. Such an approach can: (1) report prediction uncertainty, (2) be consistent with the amou...

The prediction of intelligence in preschool children using alternative models to regression.

PubMed

Finch, W Holmes; Chang, Mei; Davis, Andrew S; Holden, Jocelyn E; Rothlisberg, Barbara A; McIntosh, David E

2011-12-01

Statistical prediction of an outcome variable using multiple independent variables is a common practice in the social and behavioral sciences. For example, neuropsychologists are sometimes called upon to provide predictions of preinjury cognitive functioning for individuals who have suffered a traumatic brain injury. Typically, these predictions are made using standard multiple linear regression models with several demographic variables (e.g., gender, ethnicity, education level) as predictors. Prior research has shown conflicting evidence regarding the ability of such models to provide accurate predictions of outcome variables such as full-scale intelligence (FSIQ) test scores. The present study had two goals: (1) to demonstrate the utility of a set of alternative prediction methods that have been applied extensively in the natural sciences and business but have not been frequently explored in the social sciences and (2) to develop models that can be used to predict premorbid cognitive functioning in preschool children. Predictions of Stanford-Binet 5 FSIQ scores for preschool-aged children is used to compare the performance of a multiple regression model with several of these alternative methods. Results demonstrate that classification and regression trees provided more accurate predictions of FSIQ scores than does the more traditional regression approach. Implications of these results are discussed.

Evaluating the relationship between wildfire extent and nitrogen dry deposition in a boreal forest in interior Alaska

NASA Astrophysics Data System (ADS)

Nagano, Hirohiko; Iwata, Hiroki

2017-03-01

Alaska wildfires may play an important role in nitrogen (N) dry deposition in Alaskan boreal forests. Here we used annual N dry deposition data measured by CASTNET at Denali National Park (DEN417) during 1999-2013, to evaluate the relationships between wildfire extent and N dry deposition in Alaska. We established six potential factors for multiple regression analysis, including burned area within 100 km of DEN417 (BA100km) and in other distant parts of Alaska (BAAK), the sum of indexes of North Atlantic Oscillation and Arctic Oscillation (OI), number of days with negative OI (OIday), precipitation (PRCP), and number of days with PRCP (PRCPday). Multiple regression analysis was conducted for both time scales, annual (using only annual values of factors) and six-month (using annual values of BAAK and BA100km, and fire and non-fire seasons' values of other four factors) time scales. Together, BAAK, BA100km, and OIday, along with PRCPday in the case of the six-month scale, explained more than 92% of the interannual variation in N dry deposition. The influence of BA100km on N dry deposition was ten-fold greater than from BAAK; the qualitative contribution was almost zero, however, due to the small BA100km. BAAK was the leading explanatory factor, with a 15 ± 14% contribution. We further calculated N dry deposition during 1950-2013 using the obtained regression equation and long-term records for the factors. The N dry deposition calculated for 1950-2013 revealed that an increased occurrence of wildfires during the 2000s led to the maximum N dry deposition exhibited during this decade. As a result, the effect of BAAK on N dry deposition remains sufficiently large, even when large possible uncertainties (>40%) in the measurement of N dry deposition are taken into account for the multiple regression analysis.

Measuring the impact of multiple sclerosis on psychosocial functioning: the development of a new self-efficacy scale.

PubMed

Airlie, J; Baker, G A; Smith, S J; Young, C A

2001-06-01

To develop a scale to measure self-efficacy in neurologically impaired patients with multiple sclerosis and to assess the scale's psychometric properties. Cross-sectional questionnaire study in a clinical setting, the retest questionnaire returned by mail after completion at home. Regional multiple sclerosis (MS) outpatient clinic or the Clinical Trials Unit (CTU) at a large neuroscience centre in the UK. One hundred persons with MS attending the Walton Centre for Neurology and Neurosurgery and Clatterbridge Hospital, Wirral, as outpatients. Cognitively impaired patients were excluded at an initial clinic assessment. Patients were asked to provide demographic data and complete the self-efficacy scale along with the following validated scales: Hospital Anxiety and Depression Scale, Rosenberg Self-Esteem Scale, Impact, Stigma and Mastery and Rankin Scales. The Rankin Scale and Barthel Index were also assessed by the physician. A new 11-item self-efficacy scale was constructed consisting of two domains of control and personal agency. The validity of the scale was confirmed using Cronbach's alpha analysis of internal consistency (alpha = 0.81). The test-retest reliability of the scale over two weeks was acceptable with an intraclass correlation coefficient of 0.79. Construct validity was investigated using Pearson's product moment correlation coefficient resulting in significant correlations with depression (r= -0.52) anxiety (r =-0.50) and mastery (r= 0.73). Multiple regression analysis demonstrated that these factors accounted for 70% of the variance of scores on the self-efficacy scale, with scores on mastery, anxiety and perceived disability being independently significant. Assessment of the psychometric properties of this new self-efficacy scale suggest that it possesses good validity and reliability in patients with multiple sclerosis.

Younger age, female sex, and high number of awakenings and arousals predict fatigue in patients with sleep disorders: a retrospective polysomnographic observational study

PubMed Central

Veauthier, Christian

2013-01-01

Background The Fatigue Severity Scale (FSS) is widely used to assess fatigue, not only in the context of multiple sclerosis-related fatigue, but also in many other medical conditions. Some polysomnographic studies have shown high FSS values in sleep-disordered patients without multiple sclerosis. The Modified Fatigue Impact Scale (MFIS) has increasingly been used in order to assess fatigue, but polysomnographic data investigating sleep-disordered patients are thus far unavailable. Moreover, the pathophysiological link between sleep architecture and fatigue measured with the MFIS and the FSS has not been previously investigated. Methods This was a retrospective observational study (n = 410) with subgroups classified according to sleep diagnosis. The statistical analysis included nonparametric correlation between questionnaire results and polysomnographic data, age and sex, and univariate and multiple logistic regression. Results The multiple logistic regression showed a significant relationship between FSS/MFIS values and younger age and female sex. Moreover, there was a significant relationship between FSS values and number of arousals and between MFIS values and number of awakenings. Conclusion Younger age, female sex, and high number of awakenings and arousals are predictive of fatigue in sleep-disordered patients. Further investigations are needed to find the pathophysiological explanation for these relationships. PMID:24109185

Cooperation without Culture? The Null Effect of Generalized Trust on Intentional Homicide: A Cross-National Panel Analysis, 1995–2009

PubMed Central

Robbins, Blaine

2013-01-01

Sociologists, political scientists, and economists all suggest that culture plays a pivotal role in the development of large-scale cooperation. In this study, I used generalized trust as a measure of culture to explore if and how culture impacts intentional homicide, my operationalization of cooperation. I compiled multiple cross-national data sets and used pooled time-series linear regression, single-equation instrumental-variables linear regression, and fixed- and random-effects estimation techniques on an unbalanced panel of 118 countries and 232 observations spread over a 15-year time period. Results suggest that culture and large-scale cooperation form a tenuous relationship, while economic factors such as development, inequality, and geopolitics appear to drive large-scale cooperation. PMID:23527211

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao

2016-04-01

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

Modeling stream network-scale variation in coho salmon overwinter survival and smolt size

EPA Science Inventory

We used multiple regression and hierarchical mixed-effects models to examine spatial patterns of overwinter survival and size at smolting in juvenile coho salmon Oncorhynchus kisutch in relation to habitat attributes across an extensive stream network in southwestern Oregon over ...

Self-reports of trauma and dissociation: An examination of context effects.

PubMed

Lemons, Peter; Lynn, Steven Jay

2016-08-01

To examine context effects in moderating the link between self-reported trauma and dissociation in undergraduate samples, we administered these measures either in the same or different experimental contexts. Trauma History Screen/THS (Carlson et al., 2011)-Dissociative Experiences Scale/DES-II (Bernstein & Putnam, 1986) correlations revealed a context effect (greater correlations in same test context), although multiple regression analyses did not confirm this finding. A context effect was supported in DES-Taxon scores using multiple regression for the THS but not the Modified Posttraumatic Stress Scale (MPSS-SR; Falsetti, Resnick, Resick, & Kilpatrick, 1993), an effect confirmed with correlation comparisons. Ethnicity influenced the association between measures of trauma and dissociation. Overall, the relation between measures of trauma and dissociation was small to medium, although high correlations were observed between the DES depersonalization/derealization subscale and the Multiscale Dissociation Inventory (Briere, Weathers, & Runtz, 2005) depersonalization and derealization subscales, supporting the construct validity of these measures. Copyright © 2016 Elsevier Inc. All rights reserved.

[Childbirth pain, perinatal dissociation and perinatal distress as predictors of posttraumatic stress symptoms].

PubMed

Boudou, M; Séjourné, N; Chabrol, H

2007-11-01

This prospective, longitudinal study investigated the contributive role of childbirth pain, perinatal distress and perinatal dissociation to the development of PTSD symptoms following childbirth. One hundred and seventeen women participated at the study. The first day after delivery they completed a questionnaire to evaluate pain, the peritraumatic distress inventory (PDI) and the peritraumatic dissociative experience questionnaire (PDEQ). Six weeks after birth, they completed the impact of event scale-revised (IES-R) to measure posttraumatic stress symptoms and the Edinburgh Postnatal Depression Scale (EPDS) to assess maternal depression. A multiple regression analysis revealed that only both components of perinatal distress, life-threat perception and dysphoric emotions were significant predictors of posttraumatic stress symptoms. In another multiple regression analysis predicting dysphoric emotions, affective dimension of pain was the only significant predictor. Perinatal distress was the best predictor of posttraumatic stress symptoms. Dysphoric emotions were associated with affective dimension of pain, suggesting that women distressed by the childbirth pain would have higher risk to develop posttraumatic stress symptoms.

[Burnout syndrome and suicide risk among primary care nurses].

PubMed

Tomás-Sábado, Joaquín; Maynegre-Santaulària, Montserrat; Pérez-Bartolomé, Meritxell; Alsina-Rodríguez, Marta; Quinta-Barbero, Roser; Granell-Navas, Sergi

2010-01-01

To observe the prevalence of the burnout syndrome and the relationship with suicide risk, self-esteem, anxiety and depression, in a sample of primary care nurses. Observational, cross-sectional and correlational study. The sample consisted of 146 nursing professionals, 131 women and 15 men, with an average age of 44.02 years (SD=10.89). Participants responded to a questionnaire which included the Spanish forms of the Maslach burnout inventory (MBI), the Plutchik Suicide Risk Scale (SR), the Kuwait University Anxiety Scale (KUAS), the Self-Rating Depression Scale (SDS) and the Rosenberg Self-esteem Scale (RSES). In the inferential statistical analysis, Pearson's r coefficients and multiple linear regression were calculated. Significant correlations between suicidal risk and anxiety, depression, self-esteem, emotional exhaustion and personal performance, were obtained. In the multiple regression analysis, depression was the main predictor of suicidal risk, followed by anxiety and emotional exhaustion. The scores obtained in burnout and suicidal risk were, in general, lower than those observed in other studies, emphasising the high level observed in personal performance, which reflects reasonable professional satisfaction. The results show the important role of working atmosphere and early recognition of mental disorders in burnout and suicidal risk prevention. Copyright (c) 2009 Elsevier España, S.L. All rights reserved.

Digital literacy of youth and young adults with intellectual disability predicted by support needs and social maturity.

PubMed

Seok, Soonhwa; DaCosta, Boaventura

2017-01-01

This study investigated relationships between digital propensity and support needs as well as predictors of digital propensity in the context of support intensity, age, gender, and social maturity. A total of 118 special education teachers rated the support intensity, digital propensity, and social maturity of 352 students with intellectual disability. Leveraging the Digital Propensity Index, Supports Intensity Scale, and the Social Maturity Scale, descriptive statistics, correlations, multiple regressions, and regression analyses were employed. The findings revealed significant relationships between digital propensity and support needs. In addition, significant predictors of digital propensity were found with regard to support intensity, age, gender, and social maturity.

Time-localized wavelet multiple regression and correlation

NASA Astrophysics Data System (ADS)

Fernández-Macho, Javier

2018-02-01

This paper extends wavelet methodology to handle comovement dynamics of multivariate time series via moving weighted regression on wavelet coefficients. The concept of wavelet local multiple correlation is used to produce one single set of multiscale correlations along time, in contrast with the large number of wavelet correlation maps that need to be compared when using standard pairwise wavelet correlations with rolling windows. Also, the spectral properties of weight functions are investigated and it is argued that some common time windows, such as the usual rectangular rolling window, are not satisfactory on these grounds. The method is illustrated with a multiscale analysis of the comovements of Eurozone stock markets during this century. It is shown how the evolution of the correlation structure in these markets has been far from homogeneous both along time and across timescales featuring an acute divide across timescales at about the quarterly scale. At longer scales, evidence from the long-term correlation structure can be interpreted as stable perfect integration among Euro stock markets. On the other hand, at intramonth and intraweek scales, the short-term correlation structure has been clearly evolving along time, experiencing a sharp increase during financial crises which may be interpreted as evidence of financial 'contagion'.

Distribution patterns of the crab Ucides cordatus (Brachyura, Ucididae) at different spatial scales in subtropical mangroves of Paranaguá Bay (southern Brazil)

NASA Astrophysics Data System (ADS)

Sandrini-Neto, L.; Lana, P. C.

2012-06-01

Heterogeneity in the distribution of organisms occurs at a range of spatial scales, which may vary from few centimeters to hundreds of kilometers. The exclusion of small-scale variability from routine sampling designs may confound comparisons at larger scales and lead to inconsistent interpretation of data. Despite its ecological and social-economic importance, little is known about the spatial structure of the mangrove crab Ucides cordatus in the southwest Atlantic. Previous studies have commonly compared densities at relatively broad scales, relying on alleged distribution patterns (e.g., mangroves of distinct composition and structure). We have assessed variability patterns of U. cordatus in mangroves of Paranaguá Bay at four levels of spatial hierarchy (10 s km, km, 10 s m and m) using a nested ANOVA and variance components measures. The potential role of sediment parameters, pneumatophore density, and organic matter content in regulating observed patterns was assessed by multiple regression models. Densities of total and non-commercial size crabs varied mostly at 10 s m to km scales. Densities of commercial size crabs differed at the scales of 10 s m and 10 s km. Variance components indicated that small-scale variation was the most important, contributing up to 70% of the crab density variability. Multiple regression models could not explain the observed variations. Processes driving differences in crab abundance were not related to the measured variables. Small-scale patchy distribution has direct implications to current management practices of U. cordatus. Future studies should consider processes operating at smaller scales, which are responsible for a complex mosaic of patches within previously described patterns.

Incremental Validity in the Clinical Assessment of Early Childhood Development

ERIC Educational Resources Information Center

Liu, Xin; Zhou, Xiaobin; Lackaff, Julie

2013-01-01

The authors demonstrate the increment of clinical validity in early childhood assessment of physical impairment (PI), developmental delay (DD), and autism (AUT) using multiple standardized developmental screening measures such as performance measures and parent and teacher rating scales. Hierarchical regression and sensitivity/specificity analyses…

Overall Preference of Running Shoes Can Be Predicted by Suitable Perception Factors Using a Multiple Regression Model.

PubMed

Tay, Cheryl Sihui; Sterzing, Thorsten; Lim, Chen Yen; Ding, Rui; Kong, Pui Wah

2017-05-01

This study examined (a) the strength of four individual footwear perception factors to influence the overall preference of running shoes and (b) whether these perception factors satisfied the nonmulticollinear assumption in a regression model. Running footwear must fulfill multiple functional criteria to satisfy its potential users. Footwear perception factors, such as fit and cushioning, are commonly used to guide shoe design and development, but it is unclear whether running-footwear users are able to differentiate one factor from another. One hundred casual runners assessed four running shoes on a 15-cm visual analogue scale for four footwear perception factors (fit, cushioning, arch support, and stability) as well as for overall preference during a treadmill running protocol. Diagnostic tests showed an absence of multicollinearity between factors, where values for tolerance ranged from .36 to .72, corresponding to variance inflation factors of 2.8 to 1.4. The multiple regression model of these four footwear perception variables accounted for 77.7% to 81.6% of variance in overall preference, with each factor explaining a unique part of the total variance. Casual runners were able to rate each footwear perception factor separately, thus assigning each factor a true potential to improve overall preference for the users. The results also support the use of a multiple regression model of footwear perception factors to predict overall running shoe preference. Regression modeling is a useful tool for running-shoe manufacturers to more precisely evaluate how individual factors contribute to the subjective assessment of running footwear.

Explanatory Power of Multi-scale Physical Descriptors in Modeling Benthic Indices Across Nested Ecoregions of the Pacific Northwest

NASA Astrophysics Data System (ADS)

Holburn, E. R.; Bledsoe, B. P.; Poff, N. L.; Cuhaciyan, C. O.

2005-05-01

Using over 300 R/EMAP sites in OR and WA, we examine the relative explanatory power of watershed, valley, and reach scale descriptors in modeling variation in benthic macroinvertebrate indices. Innovative metrics describing flow regime, geomorphic processes, and hydrologic-distance weighted watershed and valley characteristics are used in multiple regression and regression tree modeling to predict EPT richness, % EPT, EPT/C, and % Plecoptera. A nested design using seven ecoregions is employed to evaluate the influence of geographic scale and environmental heterogeneity on the explanatory power of individual and combined scales. Regression tree models are constructed to explain variability while identifying threshold responses and interactions. Cross-validated models demonstrate differences in the explanatory power associated with single-scale and multi-scale models as environmental heterogeneity is varied. Models explaining the greatest variability in biological indices result from multi-scale combinations of physical descriptors. Results also indicate that substantial variation in benthic macroinvertebrate response can be explained with process-based watershed and valley scale metrics derived exclusively from common geospatial data. This study outlines a general framework for identifying key processes driving macroinvertebrate assemblages across a range of scales and establishing the geographic extent at which various levels of physical description best explain biological variability. Such information can guide process-based stratification to avoid spurious comparison of dissimilar stream types in bioassessments and ensure that key environmental gradients are adequately represented in sampling designs.

College Women's Value Orientations toward Family, Career, and Graduate School.

ERIC Educational Resources Information Center

Battle, Ann; Wigfield, Allan

2003-01-01

Scales assessing intention to attend graduate school and family/career values were completed by 216 college women. Multiple regression analyses demonstrated that components of task value (intrinsic-attainment, utility, cost) predicted graduate study intentions. Strong career orientation was positively related to the valuing of graduate education.…

Do patient and proxy agree? Long-term changes in multiple sclerosis physical impact and walking ability on patient-reported outcome scales.

PubMed

Sonder, Judith M; Balk, Lisanne J; Bosma, Libertje V A E; Polman, Chris H; Uitdehaag, Bernard M J

2014-10-01

Patient-reported outcome scales (PROs) are useful in monitoring changes in multiple sclerosis (MS) over time. Although these scales are reliable and valid measures in longitudinal studies in MS patients, it is unknown what the impact is when obtaining longitudinal data from proxies. The objective of this paper is to compare longitudinal changes in patient and proxy responses on PROs assessing physical impact of MS and walking ability. In a prospective observational study, data on the Multiple Sclerosis Impact Scale (MSIS-29 physical) and Multiple Sclerosis Walking Scale (MSWS-12) were obtained from 137 patient-proxy couples at baseline and at two-year follow-up. Demographic and disease-related variables explaining agreement or disagreement between patients and proxies were investigated using linear regression analyses. Full agreement was found in 56% (MSIS) and 62% (MSWS) of the patient-proxy couples. Complete disagreement was very rare for both scales (2% MSIS, 5% MSWS). When patients were more positive than proxies, a higher age, longer disease duration, longer patient-proxy relationship and increased levels of depression, anxiety and caregiver burden in proxies were observed. In the majority of the patient-proxy couples there was agreement. Proxies can serve as a valuable source of information, but caution remains essential when using scores from proxies. © The Author(s), 2014.

Relationship between affective determinants and achievement in science for seventeen-year-olds

NASA Astrophysics Data System (ADS)

Napier, John D.; Riley, Joseph P.

Data collected in the 1976-1977 NAEP survey of seventeen-year-olds was used to reanalyze the hypothesis that there are affective determinates of science achievement. Factor and item analysis procedures were used to examine affective and cognitive items from Booklet 4. Eight affective scales and one cognitive achievement scale were identified. Using stepwise multiple regression procedures, the four affective scales of Motivation, Anxiety, Student Choice, and Teacher Support were found to account for the majority of the correlation between the affective determinants and achievement.

The association of fatigue, pain, depression and anxiety with work and activity impairment in immune mediated inflammatory diseases.

PubMed

Enns, Murray W; Bernstein, Charles N; Kroeker, Kristine; Graff, Lesley; Walker, John R; Lix, Lisa M; Hitchon, Carol A; El-Gabalawy, Renée; Fisk, John D; Marrie, Ruth Ann

2018-01-01

Impairment in work function is a frequent outcome in patients with chronic conditions such as immune-mediated inflammatory diseases (IMID), depression and anxiety disorders. The personal and economic costs of work impairment in these disorders are immense. Symptoms of pain, fatigue, depression and anxiety are potentially remediable forms of distress that may contribute to work impairment in chronic health conditions such as IMID. The present study evaluated the association between pain [Medical Outcomes Study Pain Effects Scale], fatigue [Daily Fatigue Impact Scale], depression and anxiety [Hospital Anxiety and Depression Scale] and work impairment [Work Productivity and Activity Impairment Scale] in four patient populations: multiple sclerosis (n = 255), inflammatory bowel disease (n = 248, rheumatoid arthritis (n = 154) and a depression and anxiety group (n = 307), using quantile regression, controlling for the effects of sociodemographic factors, physical disability, and cognitive deficits. Each of pain, depression symptoms, anxiety symptoms, and fatigue individually showed significant associations with work absenteeism, presenteeism, and general activity impairment (quantile regression standardized estimates ranging from 0.3 to 1.0). When the distress variables were entered concurrently into the regression models, fatigue was a significant predictor of work and activity impairment in all models (quantile regression standardized estimates ranging from 0.2 to 0.5). These findings have important clinical implications for understanding the determinants of work impairment and for improving work-related outcomes in chronic disease.

Job stress, mentoring, psychological empowerment, and job satisfaction among nursing faculty.

PubMed

Chung, Catherine E; Kowalski, Susan

2012-07-01

The National League for Nursing endorses mentoring throughout nursing faculty's careers as the method to recruit nurses into academia and improve retention of nursing faculty within the academy. A nationwide sample of 959 full-time nursing faculty completed a descriptive survey comprising a researcher-created demographic questionnaire plus Dreher's mentoring scale, Gmelch's faculty stress index, Spreitzer's psychological empowerment scale, and the National Survey for Postsecondary Faculty's job satisfaction scale. Results showed that 40% of the sample had a current work mentor. Variables showed significant relationships to job satisfaction (p < 0.01): mentoring quality (0.229), job stress (-0.568), and psychological empowerment (0.482). Multiple regression results indicated job satisfaction was significantly influenced (p < 0.01) by the presence of a mentoring relationship, salary, tenure status, psychological empowerment, and job stress. The regression model explained 47% of the variance in job satisfaction for the sample. Copyright 2012, SLACK Incorporated.

On the relation between personality and job performance of airline pilots.

PubMed

Hormann, H J; Maschke, P

1996-01-01

The validity of a personality questionnaire for the prediction of job success of airline pilots is compared to validities of a simulator checkflight and of flying experience data. During selection, 274 pilots applying for employment with a European charter airline were examined with a multidimensional personality questionnaire (Temperature Structure Scales; TSS). Additionally, the applicants were graded in a simulator checkflight. On the basis of training records, the pilots were classified as performing at standard or below standard after about 3 years of employment in the hiring company. In a multiple-regression model, this dichotomous criterion for job success can be predicted with 73.8% accuracy through the simulator checkflight and flying experience prior to employment. By adding the personality questionnaire to the regression equation, the number of correct classifications increases to 79.3%. On average, successful pilots score substantially higher on interpersonal scales and lower on emotional scales of the TSS.

Depression is a predictor for balance in people with multiple sclerosis.

PubMed

Alghwiri, Alia A; Khalil, Hanan; Al-Sharman, Alham; El-Salem, Khalid

2018-05-26

Balance impairments are common and multifactorial among people with multiple sclerosis (MS). Depression is the most common psychological disorder in MS population and is strongly correlated with MS disease. Depression might be one of the factors that contribute to balance deficits in this population. However, the relationship between depression and balance impairments has not been explored in people with MS. To investigate the association between depression and balance impairments in people with MS. Cross sectional design was used in patients with MS. The Activities-specific Balance Confidence scale (ABC) and Berg Balance Scale (BBS) was used to assess balance. Beck Depression Inventory (BDI-II) was used to quantify depression and Kurtizki Expanded Disability Status Scale (EDSS) was utilized for the evaluation of MS disability severity. Pearson correlation coefficient was used to examine the association between depression and balance measurements. Multiple linear stepwise regressions were also conducted to find out if depression is a potential predictor for balance deficits. Seventy-five individuals with MS (Female = 69%) with a mean age (SD) of 38.8 (10) and a mean (SD) EDSS score of 3.0 (1.4) were recruited in this study. Depression was present in 53% of the patients. Depression was significantly correlated with balance measurements and EDSS. However, multiple linear stepwise regressions found that only depression and age significantly predict balance. Depression and balance were found frequent and associated in people with MS. Importantly depression was a significant predictor for balance impairments in individuals with MS. Balance rehabilitation may be hindered by depression. Therefore, depression should be evaluated and treated properly in individuals with MS. Copyright © 2018 Elsevier B.V. All rights reserved.

Body Esteem Among Women with Multiple Sclerosis and its Relationship with Demographic, Clinical and Socio-Psychological Factors.

PubMed

Wilski, M; Tasiemski, T; Dąbrowski, A

2016-06-01

The principal aim of this study was to verify if specific socio-demographic, clinical, and socio-psychological factors are correlates of body esteem in women with multiple sclerosis (MS). The study included 185 women with MS who completed the Body Esteem Scale (BES), Rosenberg Self-Esteem Scale (RSES), Multiple Sclerosis Impact Scale (MSIS-29), Brief Illness Perception Questionnaire (B-IPQ), Actually Received Support Scale (a part of the Berlin Social Support Scale), and Expanded Disability Status Scale (EDSS). The patients were recruited as a result of cooperation with the Multiple Sclerosis Rehabilitation Centre in Borne Sulinowo and Polish Society of Multiple Sclerosis. The demographic characteristics of the participants and their illness-related problems were determined with a self-report survey. A hierarchical multiple regression revealed that four factors, psychological condition (R (2) = 0.23, p ≤ 0.001), received support (R (2) = 0.28, p ≤ 0.001), personal control (R (2) = 0.30, p ≤ 0.001), and physical condition (R (2) = 0.31, p ≤ 0.001), were significant correlates of the general body esteem in our study group of women with MS. The model explained 31 % of variance in body esteem. Positive body esteem, an important component of self-esteem in women with MS, is associated with better social support, overcoming negative illness-related appraisals and improvement of psychological well-being. Subjective perception of a negative impact of MS on one's physical condition may be helpful in the identification of women with MS being at increased risk of decreased body esteem.

Pre-Service Teacher Self-Efficacy for Teaching Students with Disabilities: What Knowledge Matters?

ERIC Educational Resources Information Center

Browarnik, Brooke; Bell, Sherry Mee; McCallum, R. Steve; Smyth, Kelly; Martin, Melissa

2017-01-01

The relation between items assessing knowledge about educating students with disabilities and the Tschannen-Moran and Hoy's Teachers' Sense of Efficacy Scale (TSES; 2001) was explored for 140 preservice, general education teachers using biserial correlation coefficients and a multiple regression equation. From the data collected, 8 correlations…

Modeling stream network-scale variation in Coho salmon overwinter survival and smolt size

Treesearch

Joseph L. Ebersole; Mike E. Colvin; Parker J. Wigington; Scott G. Leibowitz; Joan P. Baker; Jana E. Compton; Bruce A. Miller; Michael A. Carins; Bruce P. Hansen; Henry R. La Vigne

2009-01-01

We used multiple regression and hierarchical mixed-effects models to examine spatial patterns of overwinter survival and size at smolting in juvenile coho salmon Oncorhynchus kisutch in relation to habitat attributes across an extensive stream network in southwestern Oregon over 3 years. Contributing basin area explained the majority of spatial...

[Aggression and related factors in elementary school students].

PubMed

Ji, Eun Sun; Jang, Mi Heui

2010-10-01

This study was done to explore the relationship between aggression and internet over-use, depression-anxiety, self-esteem, all of which are known to be behavior and psychological characteristics linked to "at-risk" children for aggression. Korean-Child Behavior Check List (K-CBCL), Korean-Internet Addiction Self-Test Scale, and Self-Esteem Scale by Rosenberg (1965) were used as measurement tools with a sample of 743, 5th-6th grade students from 3 elementary schools in Jecheon city. Chi-square, t-test, ANOVA, Pearson's correlation and stepwise multiple regression with SPSS/Win 13.0 version were used to analyze the collected data. Aggression for the elementary school students was positively correlated with internet over-use and depression-anxiety, whereas self-esteem was negatively correlated with aggression. Stepwise multiple regression analysis showed that 68.4% of the variance for aggression was significantly accounted for by internet over-use, depression-anxiety, and self-esteem. The most significant factor influencing aggression was depression-anxiety. These results suggest that earlier screening and intervention programs for depression-anxiety and internet over-use for elementary student will be helpful in preventing aggression.

A psycholinguistic database for traditional Chinese character naming.

PubMed

Chang, Ya-Ning; Hsu, Chun-Hsien; Tsai, Jie-Li; Chen, Chien-Liang; Lee, Chia-Ying

2016-03-01

In this study, we aimed to provide a large-scale set of psycholinguistic norms for 3,314 traditional Chinese characters, along with their naming reaction times (RTs), collected from 140 Chinese speakers. The lexical and semantic variables in the database include frequency, regularity, familiarity, consistency, number of strokes, homophone density, semantic ambiguity rating, phonetic combinability, semantic combinability, and the number of disyllabic compound words formed by a character. Multiple regression analyses were conducted to examine the predictive powers of these variables for the naming RTs. The results demonstrated that these variables could account for a significant portion of variance (55.8%) in the naming RTs. An additional multiple regression analysis was conducted to demonstrate the effects of consistency and character frequency. Overall, the regression results were consistent with the findings of previous studies on Chinese character naming. This database should be useful for research into Chinese language processing, Chinese education, or cross-linguistic comparisons. The database can be accessed via an online inquiry system (http://ball.ling.sinica.edu.tw/namingdatabase/index.html).

A Head-to-Head Comparison of the Personality Inventory for DSM-5 (PID-5) With the Personality Diagnostic Questionnaire-4 (PDQ-4) in Predicting the General Level of Personality Pathology Among Community Dwelling Subjects.

PubMed

Fossati, Andrea; Somma, Antonella; Borroni, Serena; Maffei, Cesare; Markon, Kristian E; Krueger, Robert F

2016-02-01

In order to evaluate if measures of DSM-5 Alternative PD Model domains predicted interview-based scores of general personality pathology when compared to self-report measures of DSM-IV Axis II/DSM-5 Section II PD criteria, 300 Italian community adults were administered the Iowa Personality Disorder Screen (IPDS) interview, the Personality Inventory for DSM-5 (PID-5), and the Personality Diagnostic Questionnaire-4+ (PDQ-4+). Multiple regression analyses showed that the five PID-5 domain scales collectively explained an adequate rate of the variance of the IPDS interview total score. This result was slightly lower than the amount of variance in the IPDS total score explained by the 10 PDQ-4+ scales. The PID-5 traits scales performed better than the PDQ-4+, although the difference was marginal. Hierarchical regression analyses revealed that the PID-5 domain and trait scales provided a moderate, but significant increase in the prediction of the general level of personality pathology above and beyond the PDQ-4+ scales.

Knowledge, attitudes and practices of hypertensive patients towards prevention and early detection of chronic kidney disease: a cross sectional study from Palestine.

PubMed

Sa'adeh, Hala H; Darwazeh, Razan N; Khalil, Amani A; Zyoud, Sa'ed H

2018-01-01

Hypertension is the second most common cause of chronic kidney disease (CKD). Therefore, the aims of the study were to assess the knowledge, attitudes and practices (KAP) of hypertensive patients towards prevention and early detection of CKD, and to determine the clinical and socio-demographic factors, which affect the KAP regarding prevention of CKD. A cross-sectional study was held using the CKD screening Index to assess the KAP of 374 hypertensive patients who were selected from multiple primary healthcare centers in Nablus, Palestine. The CKD Screening Index is formed of three scales. First, the knowledge scale was a dichotomous scale of 30 items, while the attitude scale used 5-point Likert-type scale for 18 items and finally the practice scale was measured using 4-point Likert-type scale for 12 items. Multiple linear regression analysis was used to determine the association between clinical and socio-demographic factors and practices. In total, 374 hypertensive patients participated in the study. The mean age of participants was 59.14 ± 10.4 years, (range 26-85). The median (interquartile range) of the knowledge, attitude, and practice scores of hypertensive patients towards prevention and early detection of CKD were 20 (16-23), 69 (65-72), and 39 (36-42), respectively. In multiple linear regression analysis, patients age < 65 years ( p  < 0.001) and patients with high education level ( p  = 0.009) were the only factors significantly associated with higher knowledge scores. Additionally, patients age < 65 years ( p  = 0.007), patients with high income ( p  = 0.005), and patients with high knowledge score ( p  < 0.001) were the only factors significantly associated with higher attitude scores. Furthermore, regression analysis showed that patients with higher total knowledge ( p  = 0.001) as well as higher total attitudes scores towards CKD prevention ( p  < 0.001), male gender ( p  = 0.048), and patients with normal body mass index (BMI) ( p  = 0.026) were statistically significantly associated with higher practice score towards CKD prevention. Among hypertensive patients, higher scores for total knowledge and attitudes toward prevention, male sex, and normal BMI were associated with modestly higher scores for prevention practices. Finally the findings may encourage healthcare workers to give better counseling to improve knowledge.

DeepSkeleton: Learning Multi-Task Scale-Associated Deep Side Outputs for Object Skeleton Extraction in Natural Images

NASA Astrophysics Data System (ADS)

Shen, Wei; Zhao, Kai; Jiang, Yuan; Wang, Yan; Bai, Xiang; Yuille, Alan

2017-11-01

Object skeletons are useful for object representation and object detection. They are complementary to the object contour, and provide extra information, such as how object scale (thickness) varies among object parts. But object skeleton extraction from natural images is very challenging, because it requires the extractor to be able to capture both local and non-local image context in order to determine the scale of each skeleton pixel. In this paper, we present a novel fully convolutional network with multiple scale-associated side outputs to address this problem. By observing the relationship between the receptive field sizes of the different layers in the network and the skeleton scales they can capture, we introduce two scale-associated side outputs to each stage of the network. The network is trained by multi-task learning, where one task is skeleton localization to classify whether a pixel is a skeleton pixel or not, and the other is skeleton scale prediction to regress the scale of each skeleton pixel. Supervision is imposed at different stages by guiding the scale-associated side outputs toward the groundtruth skeletons at the appropriate scales. The responses of the multiple scale-associated side outputs are then fused in a scale-specific way to detect skeleton pixels using multiple scales effectively. Our method achieves promising results on two skeleton extraction datasets, and significantly outperforms other competitors. Additionally, the usefulness of the obtained skeletons and scales (thickness) are verified on two object detection applications: Foreground object segmentation and object proposal detection.

Relation of organizational citizenship behavior and locus of control.

PubMed

Turnipseed, David L; Bacon, Calvin M

2009-12-01

The relation of organizational citizenship behavior and locus of control was assessed in a sample of 286 college students (52% men; M age = 24 yr.) who worked an average of 26 hr. per week. Measures were Spector's Work Locus of Control Scale and Podsakoff, et al.'s Organization Citizenship Behavior scale. Hierarchical multiple regressions indicated positive association of scores on work locus of control with scores on each of the four tested dimensions of organizational citizenship, as well as total organizational citizenship behavior.

Predicting Patient Advocacy Engagement: A Multiple Regression Analysis Using Data From Health Professionals in Acute-Care Hospitals.

PubMed

Jansson, Bruce S; Nyamathi, Adeline; Heidemann, Gretchen; Duan, Lei; Kaplan, Charles

2015-01-01

Although literature documents the need for hospital social workers, nurses, and medical residents to engage in patient advocacy, little information exists about what predicts the extent they do so. This study aims to identify predictors of health professionals' patient advocacy engagement with respect to a broad range of patients' problems. A cross-sectional research design was employed with a sample of 94 social workers, 97 nurses, and 104 medical residents recruited from eight hospitals in Los Angeles. Bivariate correlations explored whether seven scales (Patient Advocacy Eagerness, Ethical Commitment, Skills, Tangible Support, Organizational Receptivity, Belief Other Professionals Engage, and Belief the Hospital Empowers Patients) were associated with patient advocacy engagement, measured by the validated Patient Advocacy Engagement Scale. Regression analysis examined whether these scales, when controlling for sociodemographic and setting variables, predicted patient advocacy engagement. While all seven predictor scales were significantly associated with patient advocacy engagement in correlational analyses, only Eagerness, Skills, and Belief the Hospital Empowers Patients predicted patient advocacy engagement in regression analyses. Additionally, younger professionals engaged in higher levels of patient advocacy than older professionals, and social workers engaged in greater patient advocacy than nurses. Limitations and the utility of these findings for acute-care hospitals are discussed.

An investigation of the detection of tornadic thunderstorms by observing storm top features using geosynchronous satellite imagery

NASA Technical Reports Server (NTRS)

Anderson, Charles E.

1991-01-01

The number of tornado outbreak cases studied in detail was increased from the original 8. Detailed ground and aerial studies were carried out of two outbreak cases of considerable importance. It was demonstrated that multiple regression was able to predict the tornadic potential of a given thunderstorm cell by its cirrus anvil plume characteristics. It was also shown that the plume outflow intensity and the deviation of the plume alignment from storm relative winds at anvil altitude could account for the variance in tornadic potential for a given cell ranging from 0.37 to 0.82 for linear to values near 0.9 for quadratic regression. Several predictors were used in various discriminant analysis models and in censored regression models to obtain forecasts of whether a cell is tornadic and how strong tornadic it could be potentially. The experiments were performed with the synoptic scale vertical shear in the horizontal wind and with synoptic scale surface vorticity in the proximity of the cell.

The relationship between quality of work life and turnover intention of primary health care nurses in Saudi Arabia.

PubMed

Almalki, Mohammed J; FitzGerald, Gerry; Clark, Michele

2012-09-12

Quality of work life (QWL) has been found to influence the commitment of health professionals, including nurses. However, reliable information on QWL and turnover intention of primary health care (PHC) nurses is limited. The aim of this study was to examine the relationship between QWL and turnover intention of PHC nurses in Saudi Arabia. A cross-sectional survey was used in this study. Data were collected using Brooks' survey of Quality of Nursing Work Life, the Anticipated Turnover Scale and demographic data questions. A total of 508 PHC nurses in the Jazan Region, Saudi Arabia, completed the questionnaire (RR = 87%). Descriptive statistics, t-test, ANOVA, General Linear Model (GLM) univariate analysis, standard multiple regression, and hierarchical multiple regression were applied for analysis using SPSS v17 for Windows. Findings suggested that the respondents were dissatisfied with their work life, with almost 40% indicating a turnover intention from their current PHC centres. Turnover intention was significantly related to QWL. Using standard multiple regression, 26% of the variance in turnover intention was explained by QWL, p < 0.001, with R2 = .263. Further analysis using hierarchical multiple regression found that the total variance explained by the model as a whole (demographics and QWL) was 32.1%, p < 0.001. QWL explained an additional 19% of the variance in turnover intention, after controlling for demographic variables. Creating and maintaining a healthy work life for PHC nurses is very important to improve their work satisfaction, reduce turnover, enhance productivity and improve nursing care outcomes.

The relationship between quality of work life and turnover intention of primary health care nurses in Saudi Arabia

PubMed Central

2012-01-01

Background Quality of work life (QWL) has been found to influence the commitment of health professionals, including nurses. However, reliable information on QWL and turnover intention of primary health care (PHC) nurses is limited. The aim of this study was to examine the relationship between QWL and turnover intention of PHC nurses in Saudi Arabia. Methods A cross-sectional survey was used in this study. Data were collected using Brooks’ survey of Quality of Nursing Work Life, the Anticipated Turnover Scale and demographic data questions. A total of 508 PHC nurses in the Jazan Region, Saudi Arabia, completed the questionnaire (RR = 87%). Descriptive statistics, t-test, ANOVA, General Linear Model (GLM) univariate analysis, standard multiple regression, and hierarchical multiple regression were applied for analysis using SPSS v17 for Windows. Results Findings suggested that the respondents were dissatisfied with their work life, with almost 40% indicating a turnover intention from their current PHC centres. Turnover intention was significantly related to QWL. Using standard multiple regression, 26% of the variance in turnover intention was explained by QWL, p < 0.001, with R2 = .263. Further analysis using hierarchical multiple regression found that the total variance explained by the model as a whole (demographics and QWL) was 32.1%, p < 0.001. QWL explained an additional 19% of the variance in turnover intention, after controlling for demographic variables. Conclusions Creating and maintaining a healthy work life for PHC nurses is very important to improve their work satisfaction, reduce turnover, enhance productivity and improve nursing care outcomes. PMID:22970764

Motivators of Adult Women Enrolled in a Community College

ERIC Educational Resources Information Center

Johnston, Connie Dianne

2010-01-01

The goal of this study was to describe what motivates adult women enrolled in a community college to pursue higher education. Utilizing profile analysis and multiple regression analyses, this study investigated the extent to which gender, English as a first language, and age predicted the seven factors of the Education Participation Scale (A-form)…

High- and Low-Achieving Fraternity Environments at a Selective Institution: Their Influence on Members' Binge Drinking and GPA

ERIC Educational Resources Information Center

Maholchic-Nelson, Suzy

2010-01-01

This correlational study tested the efficacy of the social-ecological theory (Moos, 1979) by employing the University Residential Environmental Scale and multiple regression analysis to examine the influences of personal attributes (SAT, parents' level of education, race/ethnicity, and high school drinking) and environmental factors (high/low…

Analyzing the Gender Gap in Math Achievement: Evidence from a Large-Scale US Sample

ERIC Educational Resources Information Center

Cheema, Jehanzeb R.; Galluzzo, Gary

2013-01-01

The US portion of the Program for International Student Assessment (PISA) 2003 student questionnaire comprising of 4,733 observations was used in a multiple regression framework to predict math achievement from demographic variables, such as gender, race, and socioeconomic status, and two student-specific measures of perception, math anxiety and…

Ecological and Topographic Features of Volcanic Ash-Influenced Forest Soils

Treesearch

Mark Kimsey; Brian Gardner; Alan Busacca

2007-01-01

Volcanic ash distribution and thickness were determined for a forested region of north-central Idaho. Mean ash thickness and multiple linear regression analyses were used to model the effect of environmental variables on ash thickness. Slope and slope curvature relationships with volcanic ash thickness varied on a local spatial scale across the study area. Ash...

Prenatal Exposure to Alcohol, Caffeine, Tobacco, and Aspirin: Effects on Fine and Gross Motor Preformance in 4-Year-Old Children.

ERIC Educational Resources Information Center

Barr, Helen M.; And Others

1990-01-01

Multiple regression analyses of data from 449 children indicated statistically significant relationships between moderate levels of prenatal alcohol exposure and increased errors, increased latency, and increased total time on the Wisconsin Fine Motor Steadiness Battery and poorer balance on the Gross Motor Scale. (RH)

Relative importance of climate changes at different time scales on net primary productivity-a case study of the Karst area of northwest Guangxi, China.

PubMed

Liu, Huiyu; Zhang, Mingyang; Lin, Zhenshan

2017-10-05

Climate changes are considered to significantly impact net primary productivity (NPP). However, there are few studies on how climate changes at multiple time scales impact NPP. With MODIS NPP product and station-based observations of sunshine duration, annual average temperature and annual precipitation, impacts of climate changes at different time scales on annual NPP, have been studied with EEMD (ensemble empirical mode decomposition) method in the Karst area of northwest Guangxi, China, during 2000-2013. Moreover, with partial least squares regression (PLSR) model, the relative importance of climatic variables for annual NPP has been explored. The results show that (1) only at quasi 3-year time scale do sunshine duration and temperature have significantly positive relations with NPP. (2) Annual precipitation has no significant relation to NPP by direct comparison, but significantly positive relation at 5-year time scale, which is because 5-year time scale is not the dominant scale of precipitation; (3) the changes of NPP may be dominated by inter-annual variabilities. (4) Multiple time scales analysis will greatly improve the performance of PLSR model for estimating NPP. The variable importance in projection (VIP) scores of sunshine duration and temperature at quasi 3-year time scale, and precipitation at quasi 5-year time scale are greater than 0.8, indicating important for NPP during 2000-2013. However, sunshine duration and temperature at quasi 3-year time scale are much more important. Our results underscore the importance of multiple time scales analysis for revealing the relations of NPP to changing climate.

Psychosocial correlates of fatigue in multiple sclerosis.

PubMed

Schwartz, C E; Coulthard-Morris, L; Zeng, Q

1996-02-01

To explore: (1) the interrelation among the neuropsychological, psychological, and psychosocial factors and fatigue as measured by the Multidimensional Assessment of Fatigue scale, and (2) the impact of fatigue on role performance. Clinical interview with neuropsychological testing and cross-sectional study by mail. Multiple sclerosis (MS) clinic registry of a large Boston teaching hospital. 139 MS patients representing a broad range of disability. The Multidimensional Assessment of Fatigue (MAF) scale, the Extended Disability Status Scale, the Sickness Impact Profile, Rao cognitive battery, the Trailmaking Test, depression, anxiety, and social activity limitations subscales from the Arthritis Impact Measurement Scales, and the Ryff Happiness Scale. Stepwise multiple regression analyses revealed that having a low sense of environmental mastery was the best psychosocial predictor of both global fatigue and fatigue-related distress, after adjusting for sociodemographic and medical factors. Further, people who reported being more depressed tended to report more severe fatigue. Neuropsychological performance was not associated with fatigue. Fatigue was found to limit social, work, and overall role performance, but not physical role performance. People who feel that they can choose or create environments suitable to their psychic or physical conditions report less global fatigue and less fatigue-related distress, and fatigue can have an important impact on role performance. The implications of these findings for designing fatigue management interventions are discussed.

The allometry of coarse root biomass: log-transformed linear regression or nonlinear regression?

PubMed

Lai, Jiangshan; Yang, Bo; Lin, Dunmei; Kerkhoff, Andrew J; Ma, Keping

2013-01-01

Precise estimation of root biomass is important for understanding carbon stocks and dynamics in forests. Traditionally, biomass estimates are based on allometric scaling relationships between stem diameter and coarse root biomass calculated using linear regression (LR) on log-transformed data. Recently, it has been suggested that nonlinear regression (NLR) is a preferable fitting method for scaling relationships. But while this claim has been contested on both theoretical and empirical grounds, and statistical methods have been developed to aid in choosing between the two methods in particular cases, few studies have examined the ramifications of erroneously applying NLR. Here, we use direct measurements of 159 trees belonging to three locally dominant species in east China to compare the LR and NLR models of diameter-root biomass allometry. We then contrast model predictions by estimating stand coarse root biomass based on census data from the nearby 24-ha Gutianshan forest plot and by testing the ability of the models to predict known root biomass values measured on multiple tropical species at the Pasoh Forest Reserve in Malaysia. Based on likelihood estimates for model error distributions, as well as the accuracy of extrapolative predictions, we find that LR on log-transformed data is superior to NLR for fitting diameter-root biomass scaling models. More importantly, inappropriately using NLR leads to grossly inaccurate stand biomass estimates, especially for stands dominated by smaller trees.

Asymptotics of nonparametric L-1 regression models with dependent data

PubMed Central

ZHAO, ZHIBIAO; WEI, YING; LIN, DENNIS K.J.

2013-01-01

We investigate asymptotic properties of least-absolute-deviation or median quantile estimates of the location and scale functions in nonparametric regression models with dependent data from multiple subjects. Under a general dependence structure that allows for longitudinal data and some spatially correlated data, we establish uniform Bahadur representations for the proposed median quantile estimates. The obtained Bahadur representations provide deep insights into the asymptotic behavior of the estimates. Our main theoretical development is based on studying the modulus of continuity of kernel weighted empirical process through a coupling argument. Progesterone data is used for an illustration. PMID:24955016

The impact of depression on fatigue in patients with haemodialysis: a correlational study.

PubMed

Bai, Yu-Ling; Lai, Liu-Yuan; Lee, Bih-O; Chang, Yong-Yuan; Chiou, Chou-Ping

2015-07-01

To investigate the fatigue levels and important fatigue predictors for patients undergoing haemodialysis. Fatigue is a common symptom for haemodialysis patients. With its debilitating and distressing effects, it impacts patients in terms of their quality of life while also increasing their mortality rate. A descriptive correlational study. Convenience sampling was conducted at six chosen haemodialysis centres in Southern Taiwan. Data were collected via a structured questionnaire from 193 haemodialysis patients. The scales involved in this study were socio-demographic details, the Center for Epidemiologic Studies Depression Scale, and the Fatigue Scale for haemodialysis patients. Data analysis included percentages, means, standard deviations and hierarchical multiple regression analysis. The fatigue level for haemodialysis patients was in the moderate range. Results from the hierarchical multiple regression analysis indicated that age, employment status, types of medications, physical activity and depression were significant. Of those variables, depression had the greatest impact on the patients' fatigue level, accounting for up to 30·6% of the explanatory power. The total explanatory power of the regression model was 64·2%. This study determined that for haemodialysis patients, unemployment, increased age, taking more medications or lower exercise frequencies resulted in more severe depression, which translated in turn to higher levels of fatigue. Among all these factors, depression had the greatest impact on the patients' fatigue levels. Not only is this finding beneficial to future studies on fatigue as a source of reference, it is also helpful in our understanding of important predictors relating to fatigue in the everyday lives of haemodialysis patients. It is recommended that when caring for fatigued patients, more care should be dedicated to their psychological states, and assistance should be provided in a timely way so as to reduce the amount of fatigue suffered. © 2015 John Wiley & Sons Ltd.

Relationship between the clinical global impression of severity for schizoaffective disorder scale and established mood scales for mania and depression.

PubMed

Turkoz, Ibrahim; Fu, Dong-Jing; Bossie, Cynthia A; Sheehan, John J; Alphs, Larry

2013-08-15

This analysis explored the relationship between ratings on HAM-D-17 or YMRS and those on the depressive or manic subscale of CGI-S for schizoaffective disorder (CGI-S-SCA). This post hoc analysis used the database (N=614) from two 6-week, randomized, placebo-controlled studies of paliperidone ER versus placebo in symptomatic subjects with schizoaffective disorder assessed using HAM-D-17, YMRS, and CGI-S-SCA scales. Parametric and nonparametric regression models explored the relationships between ratings on YMRS and HAM-D-17 and on depressive and manic domains of the CGI-S-SCA from baseline to the 6-week end point. A clinically meaningful improvement was defined as a change of 1 point in the CGI-S-SCA score. No adjustment was made for multiplicity. Multiple linear regression models suggested that a 1-point change in the depressive domain of CGI-S-SCA corresponded to an average 3.6-point (SE=0.2) change in HAM-D-17 score. Similarly, a 1-point change in the manic domain of CGI-S-SCA corresponded to an average 5.8-point (SE=0.2) change in YMRS score. Results were confirmed using local and cumulative logistic regression models in addition to equipercentile linking. Lack of subjects scoring over the complete range of possible scores may limit broad application of the analyses. Clinically meaningful score changes in depressive and manic domains of CGI-S-SCA corresponded to approximately 4- and 6-point score changes on HAM-D-17 and YMRS, respectively, in symptomatic subjects with schizoaffective disorder. Copyright © 2013 Elsevier B.V. All rights reserved.

Obsessional personality features in employed Japanese adults with a lifetime history of depression: assessment by the Munich Personality Test (MPT).

PubMed

Sakado, K; Sakado, M; Seki, T; Kuwabara, H; Kojima, M; Sato, T; Someya, T

2001-06-01

Although a number of studies have reported on the association between obsessional personality features as measured by the Munich Personality Test (MPT) "Rigidity" scale and depression, there has been no examination of these relationships in a non-clinical sample. The dimensional scores on the MPT were compared between subjects with and without lifetime depression, using a sample of employed Japanese adults. The odds ratio for suffering from lifetime depression was estimated by multiple logistic regression analysis. To diagnose a lifetime history of depression, the Inventory to Diagnose Depression, Lifetime version (IDDL) was used. The subjects with lifetime depression scored significantly higher on the "Rigidity" scale than the subjects without lifetime depression. In our logistic regression analysis, three risk factors were identified as each independently increasing a person's risk for suffering from lifetime depression: higher levels of "Rigidity", being of the female gender, and suffering from current depressive symptoms. The MPT "Rigidity" scale is a sensitive measure of personality features that occur with depression.

Strengths use as a secret of happiness: Another dimension of visually impaired individuals' psychological state.

PubMed

Matsuguma, Shinichiro; Kawashima, Motoko; Negishi, Kazuno; Sano, Fumiya; Mimura, Masaru; Tsubota, Kazuo

2018-01-01

It is well recognized that visual impairments (VI) worsen individuals' mental condition. However, little is known about the positive aspects including subjective happiness, positive emotions, and strengths. Therefore, the purpose of this study was to investigate the positive aspects of persons with VI including their subjective happiness, positive emotions, and strengths use. Positive aspects of persons with VI were measured using the Subjective Happiness Scale (SHS), the Scale of Positive and Negative Experience-Balance (SPANE-B), and the Strengths Use Scale (SUS). A cross-sectional analysis was utilized to examine personal information in a Tokyo sample (N = 44). We used a simple regression analysis and found significant relationships between the SHS or SPANE-B and SUS; on the contrary, VI-related variables were not correlated with them. A multiple regression analysis confirmed that SUS was a significant factor associated with both the SHS and SPANE-B. Strengths use might be a possible protective factor from the negative effects of VI.

Cancer Patients Enrolled in a Smoking Cessation Clinical Trial: Characteristics and Correlates of Smoking Rate and Nicotine Dependence.

PubMed

Miele, Andrew; Thompson, Morgan; Jao, Nancy C; Kalhan, Ravi; Leone, Frank; Hogarth, Lee; Hitsman, Brian; Schnoll, Robert

2018-01-01

A substantial proportion of cancer patients continue to smoke after their diagnosis but few studies have evaluated correlates of nicotine dependence and smoking rate in this population, which could help guide smoking cessation interventions. This study evaluated correlates of smoking rate and nicotine dependence among 207 cancer patients. A cross-sectional analysis using multiple linear regression evaluated disease, demographic, affective, and tobacco-seeking correlates of smoking rate and nicotine dependence. Smoking rate was assessed using a timeline follow-back method. The Fagerström Test for Nicotine Dependence measured levels of nicotine dependence. A multiple linear regression predicting nicotine dependence showed an association with smoking to alleviate a sense of addiction from the Reasons for Smoking scale and tobacco-seeking behavior from the concurrent choice task ( p < .05), but not with affect measured by the HADS and PANAS ( p > .05). Multiple linear regression predicting prequit showed an association with smoking to alleviate addiction ( p < .05). ANOVA showed that Caucasian participants reported greater rates of smoking compared to other races. The results suggest that behavioral smoking cessation interventions that focus on helping patients to manage tobacco-seeking behavior, rather than mood management interventions, could help cancer patients quit smoking.

Estimating V0[subscript 2]max Using a Personalized Step Test

ERIC Educational Resources Information Center

Webb, Carrie; Vehrs, Pat R.; George, James D.; Hager, Ronald

2014-01-01

The purpose of this study was to develop a step test with a personalized step rate and step height to predict cardiorespiratory fitness in 80 college-aged males and females using the self-reported perceived functional ability scale and data collected during the step test. Multiple linear regression analysis yielded a model (R = 0.90, SEE = 3.43…

[Life satisfaction and related socio-demographic factors during female midlife].

PubMed

Cuadros, José Luis; Pérez-Roncero, Gonzalo R; López-Baena, María Teresa; Cuadros-Celorrio, Angela M; Fernández-Alonso, Ana María

2014-01-01

To assess life satisfaction and related factors in middle-aged Spanish women. This was a cross-sectional study including 235 women aged 40 to 65, living in Granada (Spain), healthy companions of patients visiting the obstetrics and gynecology clinics. They completed the Diener Satisfaction with Life Scale, the Menopause Rating Scale, the Perceived Stress Scale, the Insomnia Severity Index and a sociodemographic questionnaire containing personal and partner data. Internal consistency of each tool was also calculated. Almost two-thirds (61.3%) of the women were postmenopausal, and 43.8% had abdominal obesity, 36.6% had insomnia, 18.7% had poor menopause-related quality of life, 31.9% performed regular exercise, and 5.1% had severe financial problems. Life satisfaction showed significant positive correlations (Spearman's test) with female and male age, and inverse correlations with menopause-related quality of life, perceived stress and insomnia. In the multiple linear regression analysis, high life satisfaction is positively correlated with having a partner who performed exercise, and inversely with having work problems, perceived stress and the suspicion of partner infidelity. These factors explained 40% of the variance of the multiple regression analysis for life satisfaction in middle-aged women. Life satisfaction is a construct related to perceived stress, work problems, and having a partner, while aspects of menopause and general health had no significant influence. Copyright © 2014 Elsevier España, S.L.U. All rights reserved.

The influence of coping styles on long-term employment in multiple sclerosis: A prospective study.

PubMed

Grytten, Nina; Skår, Anne Br; Aarseth, Jan Harald; Assmus, Jorg; Farbu, Elisabeth; Lode, Kirsten; Nyland, Harald I; Smedal, Tori; Myhr, Kjell Morten

2017-06-01

The aim was to investigate predictive values of coping styles, clinical and demographic factors on time to unemployment in patients diagnosed with multiple sclerosis (MS) during 1998-2002 in Norway. All patients ( N = 108) diagnosed with MS 1998-2002 in Hordaland and Rogaland counties, Western Norway, were invited to participate in the long-term follow-up study in 2002. Baseline recordings included disability scoring (Expanded Disability Status Scale (EDSS)), fatigue (Fatigue Severity Scale (FSS)), depression (Beck Depression Inventory (BDI)), and questionnaire assessing coping (the Dispositional Coping Styles Scale (COPE)). Logistic regression analysis was used to identify factors associated with unemployed at baseline, and Cox regression analysis to identify factors at baseline associated with time to unemployment during follow-up. In all, 41 (44%) were employed at baseline. After 13 years follow-up in 2015, mean disease duration of 22 years, 16 (17%) were still employed. Median time from baseline to unemployment was 6 years (±5). Older age at diagnosis, female gender, and depression were associated with patients being unemployed at baseline. Female gender, long disease duration, and denial as avoidant coping strategy at baseline predicted shorter time to unemployment. Avoidant coping style, female gender, and longer disease duration were associated with shorter time to unemployment. These factors should be considered when advising patients on MS and future employment.

Family environment and its relation to adolescent personality factors.

PubMed

Forman, S G; Forman, B D

1981-04-01

Investigated the relationship between family social climate characteristics and adolescent personality functioning. The High School Personality Questionnaire (HSPQ) was administered to 80 high school students. These students and their parents also completed the Family Environment Scale (FES). Results of a stepwise multiple regression analysis indicated that one or more HSPQ scales had significant associations with each FES scale. Significant variance in child behavior was attributed to family social system functioning; however, no single family variable accounted for a major portion of the variance to the exclusion of other factors. It was concluded that child behavior varies with total system functioning, more than with separate system factors.

Variation of Annual ET Determined from Water Budgets Across Rural Southeastern Basins Differing in Forest Types

NASA Astrophysics Data System (ADS)

Younger, S. E.; Jackson, C. R.

2017-12-01

In the Southeastern United States, evapotranspiration (ET) typically accounts for 60-70% of precipitation. Watershed and plot scale experiments show that evergreen forests have higher ET rates than hardwood forests and pastures. However, some plot experiments indicate that certain hardwood species have higher ET than paired evergreens. The complexity of factors influencing ET in mixed land cover watersheds makes identifying the relative influences difficult. Previous watershed scale studies have relied on regression to understand the influences or low flow analysis to indicate growing season differences among watersheds. Existing studies in the southeast investigating ET rates for watersheds with multiple forest cover types have failed to identify a significant forest type effect, but these studies acknowledge small sample sizes. Trends of decreasing streamflow have been recognized in the region and are generally attributed to five key factors, 1.) influences from multiple droughts, 2.) changes in distribution of precipitation, 3.) reforestation of agricultural land, 4.) increasing consumptive uses, or 5.) a combination of these and other factors. This study attempts to address the influence of forest type on long term average annual streamflow and on stream low flows. Long term annual ET rates were calculated as ET = P-Q for 46 USGS gaged basins with daily data for the 1982 - 2014 water years, >40% forest cover, and no large reservoirs. Land cover data was regressed against ET to describe the relationship between each of the forest types in the National Land Cover Database. Regression analysis indicates evergreen land cover has a positive relationship with ET while deciduous and total forest have a negative relationship with ET. Low flow analysis indicates low flows tend to be lower in watersheds with more evergreen cover, and that low flows increase with increasing deciduous cover, although these relationships are noisy. This work suggests considering forest cover type improves understanding of watershed scale ET at annual and seasonal levels which is consistent with historic paired watershed experiments and some plot scale data.

Which symptoms contribute the most to patients' perception of health in multiple sclerosis?

PubMed

Green, Rivka; Cutter, Gary; Friendly, Michael; Kister, Ilya

2017-01-01

Multiple sclerosis is a polysymptomatic disease. Little is known about relative contributions of the different multiple sclerosis symptoms to self-perception of health. To investigate the relationship between symptom severity in 11 domains affected by multiple sclerosis and self-rated health. Multiple sclerosis patients in two multiple sclerosis centers assessed self-rated health with a validated instrument and symptom burden with symptoMScreen, a validated battery of Likert scales for 11 domains commonly affected by multiple sclerosis. Pearson correlations and multivariate linear regressions were used to investigate the relationship between symptoMScreen scores and self-rated health. Among 1865 multiple sclerosis outpatients (68% women, 78% with relapsing-remitting multiple sclerosis, mean age 46.38 ± 12.47 years, disease duration 13.43 ± 10.04 years), average self-rated health score was 2.30 ('moderate to good'). Symptom burden (composite symptoMScreen score) highly correlated with self-rated health ( r  = 0.68, P  < 0.0001) as did each of the symptoMScreen domain subscores. In regression analysis, pain ( t  = 7.00), ambulation ( t  = 6.91), and fatigue ( t  = 5.85) contributed the highest amount of variance in self-rated health ( P  < 0.001). Pain contributed the most to multiple sclerosis outpatients' perception of health, followed by gait dysfunction and fatigue. These findings suggest that 'invisible disability' may be more important to patients' sense of wellbeing than physical disability, and challenge the notion that physical disability should be the primary outcome measure in multiple sclerosis.

Evaluation of interpolation techniques for the creation of gridded daily precipitation (1 × 1 km2); Cyprus, 1980-2010

NASA Astrophysics Data System (ADS)

Camera, Corrado; Bruggeman, Adriana; Hadjinicolaou, Panos; Pashiardis, Stelios; Lange, Manfred A.

2014-01-01

High-resolution gridded daily data sets are essential for natural resource management and the analyses of climate changes and their effects. This study aims to evaluate the performance of 15 simple or complex interpolation techniques in reproducing daily precipitation at a resolution of 1 km2 over topographically complex areas. Methods are tested considering two different sets of observation densities and different rainfall amounts. We used rainfall data that were recorded at 74 and 145 observational stations, respectively, spread over the 5760 km2 of the Republic of Cyprus, in the Eastern Mediterranean. Regression analyses utilizing geographical copredictors and neighboring interpolation techniques were evaluated both in isolation and combined. Linear multiple regression (LMR) and geographically weighted regression methods (GWR) were tested. These included a step-wise selection of covariables, as well as inverse distance weighting (IDW), kriging, and 3D-thin plate splines (TPS). The relative rank of the different techniques changes with different station density and rainfall amounts. Our results indicate that TPS performs well for low station density and large-scale events and also when coupled with regression models. It performs poorly for high station density. The opposite is observed when using IDW. Simple IDW performs best for local events, while a combination of step-wise GWR and IDW proves to be the best method for large-scale events and high station density. This study indicates that the use of step-wise regression with a variable set of geographic parameters can improve the interpolation of large-scale events because it facilitates the representation of local climate dynamics.

Self-reported work ability and work performance in workers with chronic nonspecific musculoskeletal pain.

PubMed

de Vries, Haitze J; Reneman, Michiel F; Groothoff, Johan W; Geertzen, Jan H B; Brouwer, Sandra

2013-03-01

To assess self-reported work ability and work performance of workers who stay at work despite chronic nonspecific musculoskeletal pain (CMP), and to explore which variables were associated with these outcomes. In a cross-sectional study we assessed work ability (Work Ability Index, single item scale 0-10) and work performance (Health and Work Performance Questionnaire, scale 0-10) among 119 workers who continued work while having CMP. Scores of work ability and work performance were categorized into excellent (10), good (9), moderate (8) and poor (0-7). Hierarchical multiple regression and logistic regression analysis was used to analyze the relation of socio-demographic, pain-related, personal- and work-related variables with work ability and work performance. Mean work ability and work performance were 7.1 and 7.7 (poor to moderate). Hierarchical multiple regression analysis revealed that higher work ability scores were associated with lower age, better general health perception, and higher pain self-efficacy beliefs (R(2) = 42 %). Higher work performance was associated with lower age, higher pain self-efficacy beliefs, lower physical work demand category and part-time work (R(2) = 37 %). Logistic regression analysis revealed that work ability ≥8 was significantly explained by age (OR = 0.90), general health perception (OR = 1.04) and pain self-efficacy (OR = 1.15). Work performance ≥8 was explained by pain self-efficacy (OR = 1.11). Many workers with CMP who stay at work report poor to moderate work ability and work performance. Our findings suggest that a subgroup of workers with CMP can stay at work with high work ability and performance, especially when they have high beliefs of pain self-efficacy. Our results further show that not the pain itself, but personal and work-related factors relate to work ability and work performance.

Anxiety Levels Are Independently Associated With Cognitive Performance in an Australian Multiple Sclerosis Patient Cohort.

PubMed

Ribbons, Karen; Lea, Rodney; Schofield, Peter W; Lechner-Scott, Jeannette

2017-01-01

Neurological and psychological symptoms in multiple sclerosis can affect cognitive function. The objective of this study was to explore the relationship between psychological measures and cognitive performance in a patient cohort. In 322 multiple sclerosis patients, psychological symptoms were measured using the Depression Anxiety and Stress Scale, and cognitive function was evaluated using Audio Recorded Cognitive Screen. Multifactor linear regression analysis, accounting for all clinical covariates, found that anxiety was the only psychological measure to remain a significant predictor of cognitive performance (p<0.001), particularly memory function (p<0.001). Further prospective studies are required to determine whether treatment of anxiety improves cognitive impairment.

Post-processing ECMWF precipitation and temperature ensemble reforecasts for operational hydrologic forecasting at various spatial scales

NASA Astrophysics Data System (ADS)

Verkade, J. S.; Brown, J. D.; Reggiani, P.; Weerts, A. H.

2013-09-01

The ECMWF temperature and precipitation ensemble reforecasts are evaluated for biases in the mean, spread and forecast probabilities, and how these biases propagate to streamflow ensemble forecasts. The forcing ensembles are subsequently post-processed to reduce bias and increase skill, and to investigate whether this leads to improved streamflow ensemble forecasts. Multiple post-processing techniques are used: quantile-to-quantile transform, linear regression with an assumption of bivariate normality and logistic regression. Both the raw and post-processed ensembles are run through a hydrologic model of the river Rhine to create streamflow ensembles. The results are compared using multiple verification metrics and skill scores: relative mean error, Brier skill score and its decompositions, mean continuous ranked probability skill score and its decomposition, and the ROC score. Verification of the streamflow ensembles is performed at multiple spatial scales: relatively small headwater basins, large tributaries and the Rhine outlet at Lobith. The streamflow ensembles are verified against simulated streamflow, in order to isolate the effects of biases in the forcing ensembles and any improvements therein. The results indicate that the forcing ensembles contain significant biases, and that these cascade to the streamflow ensembles. Some of the bias in the forcing ensembles is unconditional in nature; this was resolved by a simple quantile-to-quantile transform. Improvements in conditional bias and skill of the forcing ensembles vary with forecast lead time, amount, and spatial scale, but are generally moderate. The translation to streamflow forecast skill is further muted, and several explanations are considered, including limitations in the modelling of the space-time covariability of the forcing ensembles and the presence of storages.

Reexamining the Validity and Dimensionality of the Moorong Self-Efficacy Scale: Improving Its Clinical Utility.

PubMed

Middleton, James W; Tran, Yvonne; Lo, Charles; Craig, Ashley

2016-12-01

To improve the clinical utility of the Moorong Self-Efficacy Scale (MSES) by reexamining its factor structure and comparing its performance against a measure of general self-efficacy in persons with spinal cord injury (SCI). Cross-sectional survey design. Community. Adults with SCI (N=161; 118 men and 43 women) recruited from Australia (n=82) and the United States (n=79), including 86 with paraplegia and 75 with tetraplegia. None. Confirmatory factor analysis deriving fit indices on reported 1-, 2-, and 3-factor structures for the MSES. Exploratory factor analysis of MSES using principal component analysis with promax oblique rotation and structure validation, with correlations and multiple regression using cross-sectional data from the Sherer General Self-Efficacy Scale and Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36). The MSES was confirmed to have a 3-factor structure, explaining 61% of variance. Two of the factors, labeled social function self-efficacy and personal function self-efficacy, were SCI condition-specific, whereas the other factor (accounting for 9.7% of variance) represented general self-efficacy, correlating most strongly with the Sherer General Self-Efficacy Scale. Correlations and multiple regression analyses between MSES factors, Sherer General Self-Efficacy Scale total score, SF-36 Physical and Mental Component Summary scores, and SF-36 domain scores support validity of this MSES factor structure. No significant cross-cultural differences existed between Australia and the United States in total MSES or factor scores. The findings support a 3-factor structure encompassing general and SCI domain-specific self-efficacy beliefs and better position the MSES to assist SCI rehabilitation assessment, planning, and research. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Psychometric properties of the Doloplus-2 observational pain assessment scale and comparison to self-assessment in hospitalized elderly.

PubMed

Pautex, Sophie; Herrmann, François R; Michon, Agnès; Giannakopoulos, Panteleimon; Gold, Gabriel

2007-01-01

Self-report is the "gold standard" for pain assessment, however, observational pain scales, such as Doloplus-2 must be used for patients who cannot communicate. In this follow-up study, we report the psychometric properties of the observational Doloplus-2 scale using the visual analog scale (VAS) pain score as a gold standard and evaluate its performance. Prospective clinical study of 180 hospitalized older patients who demonstrated good comprehension and reliable use of the VAS: 131 participants with dementia and 49 without. All participants assessed their chronic pain using the VAS. Doloplus-2 was independently completed by the nursing team. Mean age of patients (133 women, 47 men) was 83.7+/-6.5. Median mini-mental state examination of patients with diagnosis of dementia was 18.0+/-7.7. Nearly half of the patients (49%) reported that they experienced pain in response to a direct question. The administration of Doloplus-2 was possible in all 180 patients. Doloplus-2 correlated moderately with self-assessment (Spearman coefficient: 0.46). In a multiple regression model, Doloplus-2 predicted 41% of the variability in pain intensity measured by VAS. The somatic dimension alone explained 36% of the variance, the psychosocial bloc 5% with no better contribution of the psychomotor bloc. To shorten Doloplus-2, we constructed a version with only the 5 items that were significantly associated with the VAS score in the multiple regression models. The observational Doloplus-2 scale correlates moderately with self-assessment pain score and has adequate internal consistency. Our data also suggest that Doloplus-2 could be substantially shortened as the brief version performed similarly to the complete Doloplus-2.

Factors affecting metacognition of undergraduate nursing students in a blended learning environment.

PubMed

Hsu, Li-Ling; Hsieh, Suh-Ing

2014-06-01

This paper is a report of a study to examine the influence of demographic, learning involvement and learning performance variables on metacognition of undergraduate nursing students in a blended learning environment. A cross-sectional, correlational survey design was adopted. Ninety-nine students invited to participate in the study were enrolled in a professional nursing ethics course at a public nursing college. The blended learning intervention is basically an assimilation of classroom learning and online learning. Simple linear regression showed significant associations between frequency of online dialogues, the Case Analysis Attitude Scale scores, the Case Analysis Self Evaluation Scale scores, the Blended Learning Satisfaction Scale scores, and Metacognition Scale scores. Multiple linear regression indicated that frequency of online dialogues, the Case Analysis Self Evaluation Scale and the Blended Learning Satisfaction Scale were significant independent predictors of metacognition. Overall, the model accounted for almost half of the variance in metacognition. The blended learning module developed in this study proved successful in the end as a catalyst for the exercising of metacognitive abilities by the sample of nursing students. Learners are able to develop metacognitive ability in comprehension, argumentation, reasoning and various forms of higher order thinking through the blended learning process. © 2013 Wiley Publishing Asia Pty Ltd.

The roles of social support in helping chinese women with antenatal depressive and anxiety symptoms cope with perceived stress.

PubMed

Lau, Ying; Wong, Daniel Fu Keung; Wang, Yuqiong; Kwong, Dennis Ho Keung; Wang, Ying

2014-10-01

A community-based sample of 755 pregnant Chinese women were recruited to test the direct and moderating effects of social support in mitigating perceived stress associated with antenatal depressive or anxiety symptoms. The Social Support Rating Scale, the Perceived Stress Scale, the Edinburgh Depressive Postnatal Scale and the Zung Self-Rating Anxiety Scale were used. Social support was found to have direct effects and moderating effects on the women's perceived stress on antenatal depressive and anxiety symptoms in multiple linear regression models. This knowledge of the separate effects of social support on behavioral health is important to psychiatric nurse in planning preventive interventions. Copyright © 2014 Elsevier Inc. All rights reserved.

Impact of Sex on the Nonmotor Symptoms and the Health-Related Quality of Life in Parkinson's Disease

PubMed Central

Kovács, Márton; Makkos, Attila; Aschermann, Zsuzsanna; Janszky, József; Komoly, Sámuel; Weintraut, Rita; Karádi, Kázmér; Kovács, Norbert

2016-01-01

Background. Female Parkinson's disease (PD) patients seem to experience not only more severe motor complications and postural instability but also more pronounced depression, anxiety, pain, and sleep disturbances. Objective. The aim of the present study was to evaluate the role of sex as a possible independent predictor of HRQoL in PD. Methods. In this cross-sectional study, 621 consecutive patients treated at the University of Pécs were enrolled. Severity of PD symptoms was assessed by MDS-UPDRS, UDysRS, Non-Motor Symptoms Scale, PDSS-2, Hamilton Anxiety Scale, Montgomery-Asberg Depression Rating Scale, Lille Apathy Rating Scale, and Addenbrooke Cognitive Examination. HRQoL was assessed by PDQ-39 and EQ-5D. Multiple regression analysis was performed to estimate the PDQ-39 and EQ-5D index values based on various clinical factors. Results. Although females received significantly lower dosage of levodopa, they had significantly more disabling dyskinesia and worse postural instability. Anxiety, pain, sleep disturbances, and orthostatic symptoms were more frequent among females while sexual dysfunction, apathy, and daytime sleepiness were more severe among males. Women had worse HRQoL than men (EQ-5D index value: 0.620 ± 0.240 versus 0.663 ± 0.229, p = 0.025, and PDQ-39 SI: 27.1 ± 17.0 versus 23.5 ± 15.9, p = 0.010). Based on multiple regression analysis, sex was an independent predictor for HRQoL in PD. Conclusions. Based on our results, female sex is an independent predictor for having worse HRQoL in PD. PMID:27293959

The Relationship Between Reported Sleep Quality and Sleep Hygiene in Italian and American Adolescents

PubMed Central

LeBourgeois, Monique K.; Giannotti, Flavia; Cortesi, Flavia; Wolfson, Amy R.; Harsh, John

2014-01-01

Objective The purpose of the study was to examine the relationship between self-reported sleep quality and sleep hygiene in Italian and American adolescents and to assess whether sleep-hygiene practices mediate the relationship between culture and sleep quality. Methods Two nonprobability samples were collected from public schools in Rome, Italy, and Hattiesburg, Mississippi. Students completed the following self-report measures: Adolescent Sleep-Wake Scale, Adolescent Sleep Hygiene Scale, Pubertal Developmental Scale, and Morningness/Eveningness Scale. Results The final sample included 776 Italian and 572 American adolescents 12 to 17 years old. Italian adolescents reported much better sleep hygiene and substantially better sleep quality than American adolescents. A moderate-to-strong linear relationship was found between sleep hygiene and sleep quality in both samples. Separate hierarchical multiple regression analyses were performed on both samples. Demographic and individual characteristics explained a significant proportion of the variance in sleep quality (Italians: 18%; Americans: 25%), and the addition of sleep-hygiene domains explained significantly more variance in sleep quality (Italians: 17%; Americans: 16%). A final hierarchical multiple regression analysis with both samples combined showed that culture (Italy versus United States) only explained 0.8% of the variance in sleep quality after controlling for sleep hygiene and all other variables. Conclusions Cross-cultural differences in sleep quality, for the most part, were due to differences in sleep-hygiene practices. Sleep hygiene is an important predictor of sleep quality in Italian and American adolescents, thus supporting the implementation and evaluation of educational programs on good sleep-hygiene practices. PMID:15866860

Long-term forecasting of internet backbone traffic.

PubMed

Papagiannaki, Konstantina; Taft, Nina; Zhang, Zhi-Li; Diot, Christophe

2005-09-01

We introduce a methodology to predict when and where link additions/upgrades have to take place in an Internet protocol (IP) backbone network. Using simple network management protocol (SNMP) statistics, collected continuously since 1999, we compute aggregate demand between any two adjacent points of presence (PoPs) and look at its evolution at time scales larger than 1 h. We show that IP backbone traffic exhibits visible long term trends, strong periodicities, and variability at multiple time scales. Our methodology relies on the wavelet multiresolution analysis (MRA) and linear time series models. Using wavelet MRA, we smooth the collected measurements until we identify the overall long-term trend. The fluctuations around the obtained trend are further analyzed at multiple time scales. We show that the largest amount of variability in the original signal is due to its fluctuations at the 12-h time scale. We model inter-PoP aggregate demand as a multiple linear regression model, consisting of the two identified components. We show that this model accounts for 98% of the total energy in the original signal, while explaining 90% of its variance. Weekly approximations of those components can be accurately modeled with low-order autoregressive integrated moving average (ARIMA) models. We show that forecasting the long term trend and the fluctuations of the traffic at the 12-h time scale yields accurate estimates for at least 6 months in the future.

Use of Forest Inventory and Analysis information in wildlife habitat modeling: a process for linking multiple scales

Treesearch

Thomas C. Edwards; Gretchen G. Moisen; Tracey S. Frescino; Joshua L. Lawler

2002-01-01

We describe our collective efforts to develop and apply methods for using FIA data to model forest resources and wildlife habitat. Our work demonstrates how flexible regression techniques, such as generalized additive models, can be linked with spatially explicit environmental information for the mapping of forest type and structure. We illustrate how these maps of...

RACE AS LIVED EXPERIENCE

PubMed Central

Garcia, John A.; Sanchez, Gabriel R.; Sanchez-Youngman, Shannon; Vargas, Edward D.; Ybarra, Vickie D.

2015-01-01

A growing body of social science research has sought to conceptualize race as a multidimensional concept in which context, societal relations, and institutional dynamics are key components. Utilizing a specially designed survey, we develop and use multiple measures of race (skin color, ascribed race, and discrimination experiences) to capture race as “lived experience” and assess their impact on Latinos’ self-rated health status. We model these measures of race as a lived experience to test the explanatory power of race, both independently and as an integrated scale with categorical regression, scaling, and dimensional analyses. Our analyses show that our multiple measures of race have significant and negative effects on Latinos’ self-reported health. Skin color is a dominant factor that impacts self-reported health both directly and indirectly. We then advocate for the utilization of multiple measures of race, adding to those used in our analysis, and their application to other health and social outcomes. Our analysis provides important contributions across a wide range of health, illness, social, and political outcomes for communities of color. PMID:26681972

Relationship between alexithymia and coping strategies in patients with somatoform disorder

PubMed Central

Tominaga, Toshiyuki; Choi, Hyungin; Nagoshi, Yasuhide; Wada, Yoshihisa; Fukui, Kenji

2014-01-01

Purpose A multidimensional intervention integrating alexithymia, negative affect, and type of coping strategy is needed for the effective treatment of somatoform disorder; however, few studies have applied this approach to the three different dimensions of alexithymia in patients with somatoform disorder. The purpose of this study was to determine the relationship between type of coping strategy and three different dimensions of alexithymia expressed in patients. Patients and methods A total of 196 patients with somatoform disorder completed the 20-item Toronto Alexithymia Scale, the Zung Self-Rating Depression Scale, the Spielberger State–Trait Anxiety Inventory, the Somatosensory Amplification Scale, and the Lazarus Stress Coping Inventory. The relationships between alexithymia (Toronto Alexithymia Scale – 20 score and subscales), demographic variables, and psychological inventory scores were analyzed using Pearson’s correlation coefficients and stepwise multiple regression analysis. Results The mean Toronto Alexithymia Scale – 20 total score (56.1±10.57) was positively correlated with the number of physical symptoms as well as with psychopathology scores (Self-Rating Depression Scale, State–Trait Anxiety Inventory trait, state, and Somatosensory Amplification Scale), but negatively correlated with planful problem solving, confrontive coping, seeking social support, and positive reappraisal coping scores. With respect to coping strategy, multiple regression analyses revealed that “difficulty in identifying feelings” was positively associated with an escape–avoidance strategy, “difficulty in describing feelings” was negatively associated with a seeking social support strategy, and “externally oriented thinking” was negatively associated with a confrontive coping strategy. Conclusion Alexithymia was strongly associated with the number of somatic symptoms and negative affect. Patients with high “difficulty in describing feelings” tend to rely less on seeking social support, and patients with high “externally oriented thinking” tend to rely less on confrontive coping strategies. The coping skills intervention implemented should differ across individuals and should be based on the alexithymia dimension of each patient. PMID:24403835

Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence.

PubMed

Liu, Gang; Mukherjee, Bhramar; Lee, Seunggeun; Lee, Alice W; Wu, Anna H; Bandera, Elisa V; Jensen, Allan; Rossing, Mary Anne; Moysich, Kirsten B; Chang-Claude, Jenny; Doherty, Jennifer A; Gentry-Maharaj, Aleksandra; Kiemeney, Lambertus; Gayther, Simon A; Modugno, Francesmary; Massuger, Leon; Goode, Ellen L; Fridley, Brooke L; Terry, Kathryn L; Cramer, Daniel W; Ramus, Susan J; Anton-Culver, Hoda; Ziogas, Argyrios; Tyrer, Jonathan P; Schildkraut, Joellen M; Kjaer, Susanne K; Webb, Penelope M; Ness, Roberta B; Menon, Usha; Berchuck, Andrew; Pharoah, Paul D; Risch, Harvey; Pearce, Celeste Leigh

2018-02-01

There have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances statistical power for testing multiplicative interaction in case-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated type I error in the corresponding tests can occur. In this paper, we extend the empirical Bayes (EB) approach previously developed for multiplicative interaction, which trades off between bias and efficiency in a data-adaptive way, to the additive scale. An EB estimator of the relative excess risk due to interaction is derived, and the corresponding Wald test is proposed with a general regression setting under a retrospective likelihood framework. We study the impact of gene-environment association on the resultant test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides a gain in power compared with the standard logistic regression analysis and better control of type I error when compared with the analysis assuming gene-environment independence. We illustrate the methods with data from the Ovarian Cancer Association Consortium. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Exploring the facilitators and barriers to engagement in physical activity for people with multiple sclerosis.

PubMed

Kayes, Nicola M; McPherson, Kathryn M; Schluter, Philip; Taylor, Denise; Leete, Marta; Kolt, Gregory S

2011-01-01

To explore the relationship that cognitive behavioural and other previously identified variables have with physical activity engagement in people with multiple sclerosis (MS). This study adopted a cross-sectional questionnaire design. Participants were 282 individuals with MS. Outcome measures included the Physical Activity Disability Survey--Revised, Cognitive and Behavioural Responses to Symptoms Questionnaire, Barriers to Health Promoting Activities for Disabled Persons Scale, Multiple Sclerosis Self-efficacy Scale, Self-Efficacy for Chronic Diseases Scales and Chalder Fatigue Questionnaire. Multivariable stepwise regression analyses found that greater self-efficacy, greater reported mental fatigue and lower number of perceived barriers to physical activity accounted for a significant proportion of variance in physical activity behaviour, over that accounted for by illness-related variables. Although fear-avoidance beliefs accounted for a significant proportion of variance in the initial analyses, its effect was explained by other factors in the final multivariable analyses. Self-efficacy, mental fatigue and perceived barriers to physical activity are potentially modifiable variables which could be incorporated into interventions designed to improve physical activity engagement. Future research should explore whether a measurement tool tailored to capture beliefs about physical activity identified by people with MS would better predict participation in physical activity.

Validation of a Spanish version of the psychological inflexibility in pain scale (PIPS) and an evaluation of its relation with acceptance of pain and mindfulness in sample of persons with fibromyalgia

PubMed Central

2013-01-01

Background Psychological flexibility has been suggested as a fundamental process in health. The Psychological Inflexibility in Pain Scale (PIPS) is one of the scales employed for assessing psychological inflexibility in pain patients. The aim of this study was to validate the Spanish version of the PIPS and secondly, to compare it to two other psychological constructs, the acceptance of pain and mindfulness scales. Methods The PIPS was translated into Spanish by two bilingual linguistic experts, and then, back-translated into English to assess for equivalence. The final Spanish version was administered along with the Pain Visual Analogue Scale, Fibromyalgia Impact Questionnaire, Hospital Anxiety Depression Scale, Pain Catastrophizing Scale, Chronic Pain Acceptance Questionnaire and the Mindful Attention Awareness Scale, to 250 Spanish patients with fibromyalgia. Face validity, construct validity, reliability (internal consistency and test-retest) and convergent validity were tested. Also a multiple regression analysis was carried out.The usual guidelines have been followed for cross-cultural adaptations. Results Data were very similar to the ones obtained in the original PIPS version. The construct validity confirmed the original two-components solution which explained 61.6% of the variance. The Spanish PIPS had good test-retest reliability (intraclass correlation coefficient 0.97) and internal consistency reliability (Cronbach’s alpha: 0.90). The Spanish PIPS’ score correlated significantly with worse global functioning (r = 0.55), anxiety (r = 0.54), depression (r = 0.66), pain catastrophizing (r = 0.62), pain acceptance (r = −0.72) and mindfulness (r = −0.47), as well as correlating modestly with pain intensity (r = 0.12). The multiple regression analyses showed that psychological inflexibility, acceptance and mindfulness are not overlapped. Conclusions The Spanish PIPS scale appears to be a valid and reliable instrument for the evaluation of psychological inflexibility among a sample of fibromyalgia patients. These results ensure the use of this scale in research as well as in clinical practice. Psychological inflexibility measures processes different from other related components such as acceptance and mindfulness. PMID:23594367

Age as a moderator of relations of physical self-concept and mood changes associated with 10 weeks of programmed exercise in women.

PubMed

Annesi, James J; Westcott, Wayne L

2005-12-01

Significant correlations were found between reported changes in scores on the Physical Self-concept scale of the Tennessee Self-concept Scale, with those on the Depression (r=-.34) and Total Mood Disturbance (r=-.38) scales of the Profile of Mood States, for 35 women who initiated a structured exercise program. Accounting for age in simultaneous multiple regression equations added to the explained variance in changes in both Depression (R2=.29) and Total Mood Disturbance (R2=.18) scores. Findings supported propositions of social cognitive theory and self-efficacy theory. Limitations and the need for replication and extension were discussed.

Apportioning Sources of Riverine Nitrogen at Multiple Watershed Scales

NASA Astrophysics Data System (ADS)

Boyer, E. W.; Alexander, R. B.; Sebestyen, S. D.

2005-05-01

Loadings of reactive nitrogen (N) entering terrestrial landscapes have increased in recent decades due to anthropogenic activities associated with food and energy production. In the northeastern USA, this enhanced supply of N has been linked to many environmental concerns in both terrestrial and aquatic ecosystems, such as forest decline, lake and stream acidification, human respiratory problems, and coastal eutrophication. Thus N is a priority pollutant with regard to a whole host of air, land, and water quality issues, highlighting the need for methods to identify and quantify various N sources. Further, understanding precursor sources of N is critical to current and proposed public policies targeted at the reduction of N inputs to the terrestrial landscape and receiving waters. We present results from published and ongoing studies using multiple approaches to fingerprint sources of N in the northeastern USA, at watershed scales ranging from the headwaters to the coastal zone. The approaches include: 1) a mass balance model with a nitrogen-budgeting approach for analyses of large watersheds; 2) a spatially-referenced regression model with an empirical modeling approach for analyses of water quality at regional scales; and 3) a meta-analysis of monitoring data with a chemical tracer approach, utilizing concentrations of multiple elements and isotopic composition of N from water samples collected in the streams and rivers. We discuss the successes and limitations of these various approaches for apportioning contributions of N from multiple sources to receiving waters at regional scales.

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression

PubMed Central

Dipnall, Joanna F.

2016-01-01

Background Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. Methods The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009–2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. Results After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). Conclusion The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin. PMID:26848571

Fusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression.

PubMed

Dipnall, Joanna F; Pasco, Julie A; Berk, Michael; Williams, Lana J; Dodd, Seetal; Jacka, Felice N; Meyer, Denny

2016-01-01

Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009-2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin.

Comparison of Personal Resources in Patients Who Differently Estimate the Impact of Multiple Sclerosis.

PubMed

Wilski, Maciej; Tomczak, Maciej

2017-04-01

Discrepancies between physicians' assessment and patients' subjective representations of the disease severity may influence physician-patient communication and management of a chronic illness, such as multiple sclerosis (MS). For these reasons, it is important to recognize factors that distinguish patients who differently estimate the impact of MS. The purpose of this study was to verify if the patients who overestimate or underestimate the impact of MS differ in their perception of personal resources from individuals presenting with a realistic appraisal of their physical condition. A total of 172 women and 92 men diagnosed with MS completed Multiple Sclerosis Impact Scale, University of Washington Self Efficacy Scale, Rosenberg Self-Esteem Scale, Body Esteem Scale, Brief Illness Perception Questionnaire, Treatment Beliefs Scale, Actually Received Support Scale, and Socioeconomic resources scale. Physician's assessment of health status was determined with Expanded Disability Status Scale. Linear regression analysis was conducted to identify the subsets of patients with various patterns of subjective health and Expanded Disability Status Scale (EDSS) scores. Patients overestimating the impact of their disease presented with significantly lower levels of self-esteem, self-efficacy in MS, and body esteem; furthermore, they perceived their condition more threatening than did realists and underestimators. They also assessed anti-MS treatment worse, had less socioeconomic resources, and received less support than underestimators. Additionally, underestimators presented with significantly better perception of their disease, self, and body than did realists. Self-assessment of MS-related symptoms is associated with specific perception of personal resources in coping with the disease. These findings may facilitate communication with patients and point to new directions for future research on adaptation to MS.

Predictions for an invaded world: A strategy to predict the distribution of native and non-indigenous species at multiple scales

USGS Publications Warehouse

Reusser, D.A.; Lee, H.

2008-01-01

Habitat models can be used to predict the distributions of marine and estuarine non-indigenous species (NIS) over several spatial scales. At an estuary scale, our goal is to predict the estuaries most likely to be invaded, but at a habitat scale, the goal is to predict the specific locations within an estuary that are most vulnerable to invasion. As an initial step in evaluating several habitat models, model performance for a suite of benthic species with reasonably well-known distributions on the Pacific coast of the US needs to be compared. We discuss the utility of non-parametric multiplicative regression (NPMR) for predicting habitat- and estuary-scale distributions of native and NIS. NPMR incorporates interactions among variables, allows qualitative and categorical variables, and utilizes data on absence as well as presence. Preliminary results indicate that NPMR generally performs well at both spatial scales and that distributions of NIS are predicted as well as those of native species. For most species, latitude was the single best predictor, although similar model performance could be obtained at both spatial scales with combinations of other habitat variables. Errors of commission were more frequent at a habitat scale, with omission and commission errors approximately equal at an estuary scale. ?? 2008 International Council for the Exploration of the Sea. Published by Oxford Journals. All rights reserved.

A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield

NASA Astrophysics Data System (ADS)

Syazwan Wahab, Nur; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Amira Azmi, Nur; Che Him, Norziha; Ghazali Kamardan, M.; Ali, Maselan

2018-04-01

In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c-means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error.

[Assessment of the quality of life of patients with age-related macular degeneration after photodynamic therapy].

PubMed

Kyo, Tetsuhiro; Matsumoto, Yoko; Tochigi, Kasumi; Yuzawa, Mitsuko; Yamaguchi, Takuhiro; Komoto, Atsushi; Shimozuma, Kojiro; Fukuhara, Shunichi

2006-09-01

To quantify quality of life (QOL) changes in patients who have received a single session of photodynamic therapy (PDT) for subfoveal choroidal neovascularization, secondary to age-related macular degeneration (AMD), and to identify factors that correlate with the QOL changes. The QOL changes in 88 patients with AMD were scored with the 25-Item National Eye Institute Visual Function Questionnaire (VFQ-25) before and 3 months after a single PDT with routine ophthalmologic examinations. We used multiple regression analysis to evaluate VFQ-25 sub-scale scores and ophthalmologic findings in these patients before PDT, to identify impact on the effectiveness of PDT. We also evaluated changes in ophthalmologic findings influencing the QOL score. The sub-scale scores for both 'mental health' (p = 0.02) and 'role limitation' (p = 0.03) improved significantly in all 88 cases, but only 'mental health' improved significantly in 34 cases in which PDT was effective. Multiple regression analysis in all 88 cases revealed that the factors contributing significantly to improvement in 'mental health' were a lower pre-PDT 'mental health' score (p < 0.01) and the presence of fibrous tissue (p = 0.01) before the PDT session. The lower the role limitation before PDT (p < 0.01), the more significant was the improvement in this score. Although no baseline sub-scale score was identified as predicting the effectiveness of a single PDT session, the scores for both 'mental health' and 'role limitation' improved.

Magnetic resonance spectroscopic determination of a neuronal and axonal marker in white matter predicts reversibility of deficits in secondary normal pressure hydrocephalus

PubMed Central

Shiino, A; Nishida, Y; Yasuda, H; Suzuki, M; Matsuda, M; Inubushi, T

2004-01-01

Background: Normal pressure hydrocephalus (NPH) is considered to be a treatable form of dementia, because cerebrospinal fluid (CSF) shunting can lessen symptoms. However, neuroimaging has failed to predict when shunting will be effective. Objective: To investigate whether 1H (proton) magnetic resonance (MR) spectroscopy could predict functional outcome in patients after shunting. Methods: Neurological state including Hasegawa's dementia scale, gait, continence, and the modified Rankin scale were evaluated in 21 patients with secondary NPH who underwent ventriculo-peritoneal shunting. Outcomes were measured postoperatively at one and 12 months and were classified as excellent, fair, or poor. MR spectra were obtained from left hemispheric white matter. Results: Significant preoperative differences in N-acetyl aspartate (NAA)/creatine (Cr) and NAA/choline (Cho) were noted between patients with excellent and poor outcome at one month (p = 0.0014 and 0.0036, respectively). Multiple regression analysis linked higher preoperative NAA/Cr ratio, gait score, and modified Rankin scale to better one month outcome. Predictive value, sensitivity, and specificity for excellent outcome following shunting were 95.2%, 100%, and 87.5%. Multiple regression analysis indicated that NAA/Cho had the best predictive value for one year outcome (p = 0.0032); predictive value, sensitivity, and specificity were 89.5%, 90.0%, and 88.9%. Conclusions: MR spectroscopy predicted long term post-shunting outcomes in patients with secondary NPH, and it would be a useful assessment tool before lumbar drainage. PMID:15258216

Species Composition at the Sub-Meter Level in Discontinuous Permafrost in Subarctic Sweden

NASA Astrophysics Data System (ADS)

Anderson, S. M.; Palace, M. W.; Layne, M.; Varner, R. K.; Crill, P. M.

2013-12-01

Northern latitudes are experiencing rapid warming. Wetlands underlain by permafrost are particularly vulnerable to warming which results in changes in vegetative cover. Specific species have been associated with greenhouse gas emissions therefore knowledge of species compositional shift allows for the systematic change and quantification of emissions and changes in such emissions. Species composition varies on the sub-meter scale based on topography and other microsite environmental parameters. This complexity and the need to scale vegetation to the landscape level proves vital in our estimation of carbon dioxide (CO2) and methane (CH4) emissions and dynamics. Stordalen Mire (68°21'N, 18°49'E) in Abisko and is located at the edge of discontinuous permafrost zone. This provides a unique opportunity to analyze multiple vegetation communities in a close proximity. To do this, we randomly selected 25 1x1 meter plots that were representative of five major cover types: Semi-wet, wet, hummock, tall graminoid, and tall shrub. We used a quadrat with 64 sub plots and measured areal percent cover for 24 species. We collected ground based remote sensing (RS) at each plot to determine species composition using an ADC-lite (near infrared, red, green) and GoPro (red, blue, green). We normalized each image based on a Teflon white chip placed in each image. Textural analysis was conducted on each image for entropy, angular second momentum, and lacunarity. A logistic regression was developed to examine vegetation cover types and remote sensing parameters. We used a multiple linear regression using forwards stepwise variable selection. We found statistical difference in species composition and diversity indices between vegetation cover types. In addition, we were able to build regression model to significantly estimate vegetation cover type as well as percent cover for specific key vegetative species. This ground-based remote sensing allows for quick quantification of vegetation cover and species and also provides the framework for scaling to satellite image data to estimate species composition and shift on the landscape level. To determine diversity within our plots we calculated species richness and Shannon Index. We found that there were statistically different species composition within each vegetation cover type and also determined which species were indicative for cover type. Our logistical regression was able to significantly classify vegetation cover types based on RS parameters. Our multiple regression analysis indicated Betunla nana (Dwarf Birch) (r2= .48, p=<0.0001) and Sphagnum (r2=0.59, p=<0.0001) were statistically significant with respect to RS parameters. We suggest that ground based remote sensing methods may provide a unique and efficient method to quantify vegetation across the landscape in northern latitude wetlands.

Regional trends in short-duration precipitation extremes: a flexible multivariate monotone quantile regression approach

NASA Astrophysics Data System (ADS)

Cannon, Alex

2017-04-01

Estimating historical trends in short-duration rainfall extremes at regional and local scales is challenging due to low signal-to-noise ratios and the limited availability of homogenized observational data. In addition to being of scientific interest, trends in rainfall extremes are of practical importance, as their presence calls into question the stationarity assumptions that underpin traditional engineering and infrastructure design practice. Even with these fundamental challenges, increasingly complex questions are being asked about time series of extremes. For instance, users may not only want to know whether or not rainfall extremes have changed over time, they may also want information on the modulation of trends by large-scale climate modes or on the nonstationarity of trends (e.g., identifying hiatus periods or periods of accelerating positive trends). Efforts have thus been devoted to the development and application of more robust and powerful statistical estimators for regional and local scale trends. While a standard nonparametric method like the regional Mann-Kendall test, which tests for the presence of monotonic trends (i.e., strictly non-decreasing or non-increasing changes), makes fewer assumptions than parametric methods and pools information from stations within a region, it is not designed to visualize detected trends, include information from covariates, or answer questions about the rate of change in trends. As a remedy, monotone quantile regression (MQR) has been developed as a nonparametric alternative that can be used to estimate a common monotonic trend in extremes at multiple stations. Quantile regression makes efficient use of data by directly estimating conditional quantiles based on information from all rainfall data in a region, i.e., without having to precompute the sample quantiles. The MQR method is also flexible and can be used to visualize and analyze the nonlinearity of the detected trend. However, it is fundamentally a univariate technique, and cannot incorporate information from additional covariates, for example ENSO state or physiographic controls on extreme rainfall within a region. Here, the univariate MQR model is extended to allow the use of multiple covariates. Multivariate monotone quantile regression (MMQR) is based on a single hidden-layer feedforward network with the quantile regression error function and partial monotonicity constraints. The MMQR model is demonstrated via Monte Carlo simulations and the estimation and visualization of regional trends in moderate rainfall extremes based on homogenized sub-daily precipitation data at stations in Canada.

A new predictive indicator for development of pressure ulcers in bedridden patients based on common laboratory tests results.

PubMed

Hatanaka, N; Yamamoto, Y; Ichihara, K; Mastuo, S; Nakamura, Y; Watanabe, M; Iwatani, Y

2008-04-01

Various scales have been devised to predict development of pressure ulcers on the basis of clinical and laboratory data, such as the Braden Scale (Braden score), which is used to monitor activity and skin conditions of bedridden patients. However, none of these scales facilitates clinically reliable prediction. To develop a clinical laboratory data-based predictive equation for the development of pressure ulcers. Subjects were 149 hospitalised patients with respiratory disorders who were monitored for the development of pressure ulcers over a 3-month period. The proportional hazards model (Cox regression) was used to analyse the results of 12 basic laboratory tests on the day of hospitalisation in comparison with Braden score. Pressure ulcers developed in 38 patients within the study period. A Cox regression model consisting solely of Braden scale items showed that none of these items contributed to significantly predicting pressure ulcers. Rather, a combination of haemoglobin (Hb), C-reactive protein (CRP), albumin (Alb), age, and gender produced the best model for prediction. Using the set of explanatory variables, we created a new indicator based on a multiple logistic regression equation. The new indicator showed high sensitivity (0.73) and specificity (0.70), and its diagnostic power was higher than that of Alb, Hb, CRP, or the Braden score alone. The new indicator may become a more useful clinical tool for predicting presser ulcers than Braden score. The new indicator warrants verification studies to facilitate its clinical implementation in the future.

Southwestern USA Drought over Multiple Millennia

NASA Astrophysics Data System (ADS)

Salzer, M. W.; Kipfmueller, K. F.

2014-12-01

Severe to extreme drought conditions currently exist across much of the American West. There is increasing concern that climate change may be worsening droughts in the West and particularly the Southwest. Thus, it is important to understand the role of natural variability and to place current conditions in a long-term context. We present a tree-ring derived reconstruction of regional-scale precipitation for the Southwestern USA over several millennia. A network of 48 tree-ring chronologies from California, Nevada, Utah, Arizona, New Mexico, and Colorado was used. All of the chronologies are at least 1,000 years long. The network was subjected to data reduction through PCA and a "nested" multiple linear regression reconstruction approach. The regression model was able to capture 72% of the variance in September-August precipitation over the last 1,000 years and 53% of the variance over the first millennium of the Common Era. Variance captured and spatial coverage further declined back in time as the shorter chronologies dropped out of the model, eventually reaching 24% of variance captured at 3250 BC. Results show regional droughts on decadal- to multi-decadal scales have been prominent and persistent phenomena in the region over the last several millennia. Anthropogenic warming is likely to exacerbate the effects of future droughts on human and other biotic populations.

Trend analysis of the long-term Swiss ozone measurements

NASA Technical Reports Server (NTRS)

Staehelin, Johannes; Bader, Juerg; Gelpke, Verena

1994-01-01

Trend analyses, assuming a linear trend which started at 1970, were performed from total ozone measurements from Arosa (Switzerland, 1926-1991). Decreases in monthly mean values were statistically significant for October through April showing decreases of about 2.0-4 percent per decade. For the period 1947-91, total ozone trends were further investigated using a multiple regression model. Temperature of a mountain peak in Switzerland (Mt. Santis), the F10.7 solar flux series, the QBO series (quasi biennial oscillation), and the southern oscillation index (SOI) were included as explanatory variables. Trends in the monthly mean values were statistically significant for December through April. The same multiple regression model was applied to investigate the ozone trends at various altitudes using the ozone balloon soundings from Payerne (1967-1989) and the Umkehr measurements from Arosa (1947-1989). The results show four different vertical trend regimes: On a relative scale changes were largest in the troposphere (increase of about 10 percent per decade). On an absolute scale the largest trends were obtained in the lower stratosphere (decrease of approximately 6 per decade at an altitude of about 18 to 22 km). No significant trends were observed at approximately 30 km, whereas stratospheric ozone decreased in the upper stratosphere.

Autonomous motivation and quality of life as predictors of physical activity in patients with schizophrenia.

PubMed

Costa, Raquel; Bastos, Tânia; Probst, Michel; Seabra, André; Vilhena, Estela; Corredeira, Rui

2018-02-08

Being physically active is a complex behaviour in patients with schizophrenia. Several factors were identified as barriers to achieving active behaviours in this population. Therefore, the purpose of this study was to investigate among a number of barriers what predicts the most on physical activity (PA) in patients with schizophrenia. A total of 114 patients (28♀) with schizophrenia were included. Body mass index (BMI) was calculated. Autonomous and controlled motivation (Behavioural Regulation in Exercise Questionnaire - 3), self-esteem (Rosenberg Self-esteem scale), quality of life (World Health Organization Quality of Life Scale - Brief version) and functional exercise capacity (6-minute walk test - 6MWT) were evaluated. Multiple Regression Analysis was applied to assess the effect of these variables on Total PA per week (International Physical Activity Questionnaire - short version). Autonomous motivation and domains of quality of life were positively correlated with Total PA per week. Stepwise multiple regression analyses showed that of all the candidate factors to predict PA, autonomous motivation and global domain of quality of life were found as significant predictors. Our findings help to understand the importance of autonomous motivation and quality of life for PA in patients with schizophrenia. Knowledge about these predictors may provide guidance to improve PA behaviour in this population.

Obsessive-compulsive and posttraumatic stress symptoms among civilian survivors of war.

PubMed

Morina, Naser; Sulaj, Vita; Schnyder, Ulrich; Klaghofer, Richard; Müller, Julia; Martin-Sölch, Chantal; Rufer, Michael

2016-04-27

Several psychological sequelae have been identified in civilian war survivors. However, little is known about the prevalence of obsessive-compulsive symptoms and their relationship to trauma in this population. Fifty-one adult civilian survivors of the Kosovo War (28 males) who had immigrated to Switzerland completed the Revised Obsessive-Compulsive Inventory Scale, the Posttraumatic Stress Diagnostic Scale and the Hopkins Symptom Checklist. Data were analysed using multiple regression analyses. Overall, 35 and 39% of the sample scored above the cut-offs for likely obsessive-compulsive disorder and posttraumatic stress disorder, respectively. Participants with high levels of posttraumatic stress symptoms were significantly more likely to have obsessive-compulsive symptoms, and vice versa. In multiple regression analysis, gender and severity of posttraumatic stress symptoms were predictors of obsessive-compulsive symptoms, whereas number of traumatic life event types and depressive symptoms were not. Given the small sample size, the results of this study need to be interpreted cautiously. Nevertheless, a surprisingly high number of participants in our study suffered from both obsessive-compulsive and posttraumatic stress symptoms, with obsessive-compulsive symptoms tending to be more pronounced in women. It remains, therefore, critical to specifically assess both obsessive-compulsive and posttraumatic stress symptoms in civilian war survivors, and to provide persons afflicted with appropriate mental health care.

Searching for a neurologic injury's Wechsler Adult Intelligence Scale-Third Edition profile.

PubMed

Gonçalves, Marta A; Moura, Octávio; Castro-Caldas, Alexandre; Simões, Mário R

2017-01-01

This study aimed to investigate the presence of a Wechsler Adult Intelligence Scale-Third Edition (WAIS-III) cognitive profile in a Portuguese neurologic injured sample. The Portuguese WAIS-III was administered to 81 mixed neurologic patients and 81 healthy matched controls selected from the Portuguese standardization sample. Although the mixed neurologic injury group performed significantly lower than the healthy controls for the majority of the WAIS-III scores (i.e., composite measures, discrepancies, and subtests), the mean scores were within the normal range and, therefore, at risk of being unobserved in a clinical evaluation. ROC curves analysis showed poor to acceptable diagnostic accuracy for the WAIS-III composite measures and subtests (Working Memory Index and Digit Span revealed the highest accuracy for discriminating between participants, respectively). Multiple regression analysis showed that both literacy and the presence of brain injury were significant predictors for all of the composite measures. In addition, multiple regression analysis also showed that literacy, age of injury onset, and years of survival predicted all seven composite measures for the mixed neurologic injured group. Despite the failure to find a WAIS-III cognitive profile for mixed neurologic patients, the results showed a significant influence of brain lesion and literacy in the performance of the WAIS-III.

Use of a pretest strategy for physical therapist assistant programs to predict success rate on the national physical therapy exam.

PubMed

Sloas, Stacey B; Keith, Becky; Whitehead, Malcolm T

2013-01-01

This study investigated a pretest strategy that identified physical therapist assistant (PTA) students who were at risk of failure on the National Physical Therapy Examination (NPTE). Program assessment data from five cohorts of PTA students (2005-2009) were used to develop a stepwise multiple regression formula that predicted first-time NPTE licensure scores. Data used included the Nelson-Denny Reading Test, grades from eight core courses, grade point average upon admission to the program, and scores from three mock NPTE exams given during the program. Pearson correlation coefficients were calculated between each of the 15 variables and NPTE scores. Stepwise multiple regression analysis was performed using data collected at the ends of the first, second, and third (final) semesters of the program. Data from the class of 2010 were then used to validate the formula. The end-of-program formula accounted for the greatest variance (57%) in predicted scores. Those students scoring below a predicted scaled score of 620 were identified to be at risk of failure of the licensure exam. These students were counseled, and a remedial plan was developed based on regression predictions prior to them sitting for the licensure exam.

Multiple balance tests improve the assessment of postural stability in subjects with Parkinson's disease

PubMed Central

Jacobs, J V; Horak, F B; Tran, V K; Nutt, J G

2006-01-01

Objectives Clinicians often base the implementation of therapies on the presence of postural instability in subjects with Parkinson's disease (PD). These decisions are frequently based on the pull test from the Unified Parkinson's Disease Rating Scale (UPDRS). We sought to determine whether combining the pull test, the one‐leg stance test, the functional reach test, and UPDRS items 27–29 (arise from chair, posture, and gait) predicts balance confidence and falling better than any test alone. Methods The study included 67 subjects with PD. Subjects performed the one‐leg stance test, the functional reach test, and the UPDRS motor exam. Subjects also responded to the Activities‐specific Balance Confidence (ABC) scale and reported how many times they fell during the previous year. Regression models determined the combination of tests that optimally predicted mean ABC scores or categorised fall frequency. Results When all tests were included in a stepwise linear regression, only gait (UPDRS item 29), the pull test (UPDRS item 30), and the one‐leg stance test, in combination, represented significant predictor variables for mean ABC scores (r2 = 0.51). A multinomial logistic regression model including the one‐leg stance test and gait represented the model with the fewest significant predictor variables that correctly identified the most subjects as fallers or non‐fallers (85% of subjects were correctly identified). Conclusions Multiple balance tests (including the one‐leg stance test, and the gait and pull test items of the UPDRS) that assess different types of postural stress provide an optimal assessment of postural stability in subjects with PD. PMID:16484639

Factors Associated with Metabolic Syndrome and Related Medical Costs by the Scale of Enterprise in Korea

PubMed Central

2013-01-01

Objectives The purpose of this study was to identify the risk factors of metabolic syndrome (MS) and to analyze the relationship between the risk factors of MS and medical cost of major diseases related to MS in Korean workers, according to the scale of the enterprise. Methods Data was obtained from annual physical examinations, health insurance qualification and premiums, and health insurance benefits of 4,094,217 male and female workers who underwent medical examinations provided by the National Health Insurance Corporation in 2009. Logistic regression analyses were used to the identify risk factors of MS and multiple regression was used to find factors associated with medical expenditures due to major diseases related to MS. Result The study found that low-income workers were more likely to work in small-scale enterprises. The prevalence rate of MS in males and females, respectively, was 17.2% and 9.4% in small-scale enterprises, 15.9% and 8.9% in medium-scale enterprises, and 15.9% and 5.5% in large-scale enterprises. The risks of MS increased with age, lower income status, and smoking in small-scale enterprise workers. The medical costs increased in workers with old age and past smoking history. There was also a gender difference in the pattern of medical expenditures related to MS. Conclusions Health promotion programs to manage metabolic syndrome should be developed to focus on workers who smoke, drink, and do little exercise in small scale enterprises. PMID:24472134

Factors associated with metabolic syndrome and related medical costs by the scale of enterprise in Korea.

PubMed

Kong, Hyung-Sik; Lee, Kang-Sook; Yim, Eun-Shil; Lee, Seon-Young; Cho, Hyun-Young; Lee, Bin Na; Park, Jee Young

2013-10-21

The purpose of this study was to identify the risk factors of metabolic syndrome (MS) and to analyze the relationship between the risk factors of MS and medical cost of major diseases related to MS in Korean workers, according to the scale of the enterprise. Data was obtained from annual physical examinations, health insurance qualification and premiums, and health insurance benefits of 4,094,217 male and female workers who underwent medical examinations provided by the National Health Insurance Corporation in 2009. Logistic regression analyses were used to the identify risk factors of MS and multiple regression was used to find factors associated with medical expenditures due to major diseases related to MS. The study found that low-income workers were more likely to work in small-scale enterprises. The prevalence rate of MS in males and females, respectively, was 17.2% and 9.4% in small-scale enterprises, 15.9% and 8.9% in medium-scale enterprises, and 15.9% and 5.5% in large-scale enterprises. The risks of MS increased with age, lower income status, and smoking in small-scale enterprise workers. The medical costs increased in workers with old age and past smoking history. There was also a gender difference in the pattern of medical expenditures related to MS. Health promotion programs to manage metabolic syndrome should be developed to focus on workers who smoke, drink, and do little exercise in small scale enterprises.

Relationship between cognitive emotion regulation, social support, resilience and acute stress responses in Chinese soldiers: Exploring multiple mediation model.

PubMed

Cai, Wen-Peng; Pan, Yu; Zhang, Shui-Miao; Wei, Cun; Dong, Wei; Deng, Guang-Hui

2017-10-01

The current study aimed to explore the association of cognitive emotion regulation, social support, resilience and acute stress responses in Chinese soldiers and to understand the multiple mediation effects of social support and resilience on the relationship between cognitive emotion regulation and acute stress responses. A total of 1477 male soldiers completed mental scales, including the cognitive emotion regulation questionnaire-Chinese version, the perceived social support scale, the Chinese version of the Connor-Davidson resilience scale, and the military acute stress scale. As hypothesized, physiological responses, psychological responses, and acute stress were associated with negative-focused cognitive emotion regulation, and negatively associated with positive-focused cognitive emotion regulation, social supports and resilience. Besides, positive-focused cognitive emotion regulation, social support, and resilience were significantly associated with one another, and negative-focused cognitive emotion regulation was negatively associated with social support. Regression analysis and bootstrap analysis showed that social support and resilience had partly mediating effects on negative strategies and acute stress, and fully mediating effects on positive strategies and acute stress. These results thus indicate that military acute stress is significantly associated with cognitive emotion regulation, social support, and resilience, and that social support and resilience have multiple mediation effects on the relationship between cognitive emotion regulation and acute stress responses. Copyright © 2017 Elsevier B.V. All rights reserved.

Resistance of nickel-chromium-aluminum alloys to cyclic oxidation at 1100 C and 1200 C

NASA Technical Reports Server (NTRS)

Barrett, C. A.; Lowell, C. E.

1976-01-01

Nickel-rich alloys in the Ni-Cr-Al system were evaluated for cyclic oxidation resistance in still air at 1,100 and 1,200 C. A first approximation oxidation attack parameter Ka was derived from specific weight change data involving both a scaling growth constant and a spalling constant. An estimating equation was derived with Ka as a function of the Cr and Al content by multiple linear regression and translated into countour ternary diagrams showing regions of minimum attack. An additional factor inferred from the regression analysis was that alloys melted in zirconia crucibles had significantly greater oxidation resistance than comparable alloys melted otherwise.

Feminist identity as a predictor of eating disorder diagnostic status.

PubMed

Green, Melinda A; Scott, Norman A; Riopel, Cori M; Skaggs, Anna K

2008-06-01

Passive Acceptance (PA) and Active Commitment (AC) subscales of the Feminist Identity Development Scale (FIDS) were examined as predictors of eating disorder diagnostic status as assessed by the Questionnaire for Eating Disorder Diagnoses (Q-EDD). Results of a hierarchical regression analysis revealed PA and AC scores were not statistically significant predictors of ED diagnostic status after controlling for diagnostic subtype. Results of a multiple regression analysis revealed FIDS as a statistically significant predictor of ED diagnostic status when failing to control for ED diagnostic subtype. Discrepancies suggest ED diagnostic subtype may serve as a moderator variable in the relationship between ED diagnostic status and FIDS. (c) 2008 Wiley Periodicals, Inc.

Estimating standard errors in feature network models.

PubMed

Frank, Laurence E; Heiser, Willem J

2007-05-01

Feature network models are graphical structures that represent proximity data in a discrete space while using the same formalism that is the basis of least squares methods employed in multidimensional scaling. Existing methods to derive a network model from empirical data only give the best-fitting network and yield no standard errors for the parameter estimates. The additivity properties of networks make it possible to consider the model as a univariate (multiple) linear regression problem with positivity restrictions on the parameters. In the present study, both theoretical and empirical standard errors are obtained for the constrained regression parameters of a network model with known features. The performance of both types of standard error is evaluated using Monte Carlo techniques.

[Correlations Between Joint Proprioception, Muscle Strength, and Functional Ability in Patients with Knee Osteoarthritis].

PubMed

Chen, Yoa; Yu, Yong; He, Cheng-qi

2015-11-01

To establish correlations between joint proprioception, muscle flexion and extension peak torque, and functional ability in patients with knee osteoarthritis (OA). Fifty-six patients with symptomatic knee OA were recruited in this study. Both proprioceptive acuity and muscle strength were measured using the isomed-2000 isokinetic dynamometer. Proprioceptive acuity was evaluated by establishing the joint motion detection threshold (JMDT). Muscle strength was evaluated by Max torque (Nm) and Max torque/weight (Nm/ kg). Functional ability was assessed by the Western Ontario and McMaster Universities Osteoarthritis Index physical function (WOMAC-PF) questionnaire. Correlational analyses were performed between proprioception, muscle strength, and functional ability. A multiple stepwise regression model was established, with WOMAC-PF as dependent variable and patient age, body mass index (BMI), visual analogue scale (VAS)-score, mean grade for Kellgren-Lawrance of both knees, mean strength for quadriceps and hamstring muscles of both knees, and mean JMDT of both knees as independent variables. Poor proprioception (high JMDT) was negatively correlated with muscle strength (P<0.05). There was no significant correlation between knee proprioception (high JMDT) and joint pain (WOMAC pain score), and between knee proprioception (high JMDT) and joint stiffness (WOMAC stiffness score). Poor proprioception (high JMDT) was correlated with limitation in functional ability (WOMAC physical function score r=0.659, P<0.05). WOMAC score was correlated with poor muscle strength (quadriceps muscle strength r = -0.511, P<0.05, hamstring muscle strength r = -0.408, P<0.05). The multiple stepwise regression model showed that high JMDT C standard partial regression coefficient (B) = 0.385, P<0.50 and high VAS-scale score (B=0.347, P<0.05) were significant predictors of WOMAC-PF score. Patients with poor proprioception is associated with poor muscle strength and limitation in functional ability. Patients with symptomatic OA of knees commonly endure with moderate to considerable dysfunction, which is associated with poor proprioception (high JMDT) and high VAS-scale score.

Comparing two self-report measures of coping--the Sense of Coherence Scale and the Defense Style Questionnaire.

PubMed

Sammallahti, P R; Holi, M J; Komulainen, E J; Aalberg, V A

1996-09-01

Antonovsky's Sense of Coherence Scale (SOC) and Bond's Defense Style Questionnaire (DSQ) were compared in a sample of 334 community controls and 122 psychiatric outpatients. The major question was, whether the two coping inventories with different theoretical backgrounds-stress research vs. psycho-analysis-tap similar phenomena. The affinity of the two coping measures was evident: in multiple regression analysis defenses explained 68% of the variance in sense of coherence. Not surprisingly, the SOC scale-emerging out of the salutogenic orientation-showed more expertise in measuring how people manage when they do well, whereas the DSQ-with its theoretical roots deep in psychopathology-was most sensitive to how people manage when they do rather poorly.

Multiple Correlation versus Multiple Regression.

ERIC Educational Resources Information Center

Huberty, Carl J.

2003-01-01

Describes differences between multiple correlation analysis (MCA) and multiple regression analysis (MRA), showing how these approaches involve different research questions and study designs, different inferential approaches, different analysis strategies, and different reported information. (SLD)

Locomotive syndrome is associated not only with physical capacity but also degree of depression.

PubMed

Ikemoto, Tatsunori; Inoue, Masayuki; Nakata, Masatoshi; Miyagawa, Hirofumi; Shimo, Kazuhiro; Wakabayashi, Toshiko; Arai, Young-Chang P; Ushida, Takahiro

2016-05-01

Reports of locomotive syndrome (LS) have recently been increasing. Although physical performance measures for LS have been well investigated to date, studies including psychiatric assessment are still scarce. Hence, the aim of this study was to investigate both physical and mental parameters in relation to presence and severity of LS using a 25-question geriatric locomotive function scale (GLFS-25) questionnaire. 150 elderly people aged over 60 years who were members of our physical-fitness center and displayed well-being were enrolled in this study. Firstly, using the previously determined GLFS-25 cutoff value (=16 points), subjects were divided into two groups accordingly: an LS and non-LS group in order to compare each parameter (age, grip strength, timed-up-and-go test (TUG), one-leg standing with eye open, back muscle and leg muscle strength, degree of depression and cognitive impairment) between the groups using the Mann-Whitney U-test followed by multiple logistic regression analysis. Secondly, a multiple linear regression was conducted to determine which variables showed the strongest correlation with severity of LS. We confirmed 110 people for non-LS (73%) and 40 people for LS using the GLFS-25 cutoff value. Comparative analysis between LS and non-LS revealed significant differences in parameters in age, grip strength, TUG, one-leg standing, back muscle strength and degree of depression (p < 0.006, after Bonferroni correction). Multiple logistic regression revealed that functional decline in grip strength, TUG and one-leg standing and degree of depression were significantly associated with LS. On the other hand, we observed that the significant contributors towards the GLFS-25 score were TUG and degree of depression in multiple linear regression analysis. The results indicate that LS is associated with not only the capacity of physical performance but also the degree of depression although most participants fell under the criteria of LS. Copyright © 2016 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

The Detection and Interpretation of Interaction Effects between Continuous Variables in Multiple Regression.

ERIC Educational Resources Information Center

Jaccard, James; And Others

1990-01-01

Issues in the detection and interpretation of interaction effects between quantitative variables in multiple regression analysis are discussed. Recent discussions associated with problems of multicollinearity are reviewed in the context of the conditional nature of multiple regression with product terms. (TJH)

Factors predicting work outcome in Japanese patients with schizophrenia: role of multiple functioning levels.

PubMed

Sumiyoshi, Chika; Harvey, Philip D; Takaki, Manabu; Okahisa, Yuko; Sato, Taku; Sora, Ichiro; Nuechterlein, Keith H; Subotnik, Kenneth L; Sumiyoshi, Tomiki

2015-09-01

Functional outcomes in individuals with schizophrenia suggest recovery of cognitive, everyday, and social functioning. Specifically improvement of work status is considered to be most important for their independent living and self-efficacy. The main purposes of the present study were 1) to identify which outcome factors predict occupational functioning, quantified as work hours, and 2) to provide cut-offs on the scales for those factors to attain better work status. Forty-five Japanese patients with schizophrenia and 111 healthy controls entered the study. Cognition, capacity for everyday activities, and social functioning were assessed by the Japanese versions of the MATRICS Cognitive Consensus Battery (MCCB), the UCSD Performance-based Skills Assessment-Brief (UPSA-B), and the Social Functioning Scale Individuals' version modified for the MATRICS-PASS (Modified SFS for PASS), respectively. Potential factors for work outcome were estimated by multiple linear regression analyses (predicting work hours directly) and a multiple logistic regression analyses (predicting dichotomized work status based on work hours). ROC curve analyses were performed to determine cut-off points for differentiating between the better- and poor work status. The results showed that a cognitive component, comprising visual/verbal learning and emotional management, and a social functioning component, comprising independent living and vocational functioning, were potential factors for predicting work hours/status. Cut-off points obtained in ROC analyses indicated that 60-70% achievements on the measures of those factors were expected to maintain the better work status. Our findings suggest that improvement on specific aspects of cognitive and social functioning are important for work outcome in patients with schizophrenia.

Assessing interactions between HLA-DRB1*15 and infectious mononucleosis on the risk of multiple sclerosis.

PubMed

Disanto, Giulio; Hall, Carolina; Lucas, Robyn; Ponsonby, Anne-Louise; Berlanga-Taylor, Antonio J; Giovannoni, Gavin; Ramagopalan, Sreeram V

2013-09-01

Gene-environment interactions may shed light on the mechanisms underlying multiple sclerosis (MS). We pooled data from two case-control studies on incident demyelination and used different methods to assess interaction between HLA-DRB1*15 (DRB1-15) and history of infectious mononucleosis (IM). Individuals exposed to both factors were at substantially increased risk of disease (OR=7.32, 95% CI=4.92-10.90). In logistic regression models, DRB1-15 and IM status were independent predictors of disease while their interaction term was not (DRB1-15*IM: OR=1.35, 95% CI=0.79-2.23). However, interaction on an additive scale was evident (Synergy index=2.09, 95% CI=1.59-2.59; excess risk due to interaction=3.30, 95%CI=0.47-6.12; attributable proportion due to interaction=45%, 95% CI=22-68%). This suggests, if the additive model is appropriate, the DRB1-15 and IM may be involved in the same causal process leading to MS and highlights the benefit of reporting gene-environment interactions on both a multiplicative and additive scale.

Community integration following multidisciplinary rehabilitation for traumatic brain injury.

PubMed

Goranson, Tamara E; Graves, Roger E; Allison, Deborah; La Freniere, Ron

2003-09-01

To determine the extent to which participation in a multidisciplinary rehabilitation programme and patient characteristics predict improvement in community integration following mild-to-moderate traumatic brain injury (TBI). A non-randomized case-control study was conducted employing a pre-test-post-test multiple regression design. Archival data for 42 patients with mild-to-moderate TBI who completed the Community Integration Questionnaire (CIQ) at intake and again 6-18 months later were analysed. Half the sample participated in an intensive outpatient rehabilitation programme that provided multi-modal interventions, while the other half received no rehabilitation. The two groups were matched on age, education and time since injury. On the CIQ Home Integration scale, participation in rehabilitation and female gender predicted better outcome. On the Productivity scale, patients with a lower age at injury had better outcome. Outcome on both of these scales, as well as on the Social Integration scale, was predicted by the baseline pre-test score (initial severity). Overall, multidisciplinary rehabilitation appeared to increase personal independence. It is also concluded that: (1) multivariate analysis can reveal the relative importance of multiple predictors of outcome; (2) different predictors may predict different aspects of outcome; and (3) more sensitive and specific outcome measures are needed.

Gender, Religiosity, Sexual Activity, Sexual Knowledge, and Attitudes Toward Controversial Aspects of Sexuality.

PubMed

Sümer, Zeynep Hatipoğlu

2015-12-01

The purpose of this study is to examine the role of gender, religiosity, sexual activity, and sexual knowledge in predicting attitudes toward controversial aspects of sexuality among Turkish university students. Participants were 162 female and 135 male undergraduate students who were recruited on a volunteer basis from an urban state university in Turkey. The SKAT-A Attitude Scale along with background information form, sexual activities inventory, and sexual knowledge scale were administered to the participants. Simultaneous multiple regression analyses revealed that religiosity, particularly attendance to religious services was the most significant predictor in explaining university students' attitudes toward masturbation, abortion, homosexuality, pornography, and sexual coercion.

Beyond Multiple Regression: Using Commonality Analysis to Better Understand R[superscript 2] Results

ERIC Educational Resources Information Center

Warne, Russell T.

2011-01-01

Multiple regression is one of the most common statistical methods used in quantitative educational research. Despite the versatility and easy interpretability of multiple regression, it has some shortcomings in the detection of suppressor variables and for somewhat arbitrarily assigning values to the structure coefficients of correlated…

Multiplication factor versus regression analysis in stature estimation from hand and foot dimensions.

PubMed

Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha

2012-05-01

Estimation of stature is an important parameter in identification of human remains in forensic examinations. The present study is aimed to compare the reliability and accuracy of stature estimation and to demonstrate the variability in estimated stature and actual stature using multiplication factor and regression analysis methods. The study is based on a sample of 246 subjects (123 males and 123 females) from North India aged between 17 and 20 years. Four anthropometric measurements; hand length, hand breadth, foot length and foot breadth taken on the left side in each subject were included in the study. Stature was measured using standard anthropometric techniques. Multiplication factors were calculated and linear regression models were derived for estimation of stature from hand and foot dimensions. Derived multiplication factors and regression formula were applied to the hand and foot measurements in the study sample. The estimated stature from the multiplication factors and regression analysis was compared with the actual stature to find the error in estimated stature. The results indicate that the range of error in estimation of stature from regression analysis method is less than that of multiplication factor method thus, confirming that the regression analysis method is better than multiplication factor analysis in stature estimation. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

A secure distributed logistic regression protocol for the detection of rare adverse drug events

PubMed Central

El Emam, Khaled; Samet, Saeed; Arbuckle, Luk; Tamblyn, Robyn; Earle, Craig; Kantarcioglu, Murat

2013-01-01

Background There is limited capacity to assess the comparative risks of medications after they enter the market. For rare adverse events, the pooling of data from multiple sources is necessary to have the power and sufficient population heterogeneity to detect differences in safety and effectiveness in genetic, ethnic and clinically defined subpopulations. However, combining datasets from different data custodians or jurisdictions to perform an analysis on the pooled data creates significant privacy concerns that would need to be addressed. Existing protocols for addressing these concerns can result in reduced analysis accuracy and can allow sensitive information to leak. Objective To develop a secure distributed multi-party computation protocol for logistic regression that provides strong privacy guarantees. Methods We developed a secure distributed logistic regression protocol using a single analysis center with multiple sites providing data. A theoretical security analysis demonstrates that the protocol is robust to plausible collusion attacks and does not allow the parties to gain new information from the data that are exchanged among them. The computational performance and accuracy of the protocol were evaluated on simulated datasets. Results The computational performance scales linearly as the dataset sizes increase. The addition of sites results in an exponential growth in computation time. However, for up to five sites, the time is still short and would not affect practical applications. The model parameters are the same as the results on pooled raw data analyzed in SAS, demonstrating high model accuracy. Conclusion The proposed protocol and prototype system would allow the development of logistic regression models in a secure manner without requiring the sharing of personal health information. This can alleviate one of the key barriers to the establishment of large-scale post-marketing surveillance programs. We extended the secure protocol to account for correlations among patients within sites through generalized estimating equations, and to accommodate other link functions by extending it to generalized linear models. PMID:22871397

A secure distributed logistic regression protocol for the detection of rare adverse drug events.

PubMed

El Emam, Khaled; Samet, Saeed; Arbuckle, Luk; Tamblyn, Robyn; Earle, Craig; Kantarcioglu, Murat

2013-05-01

There is limited capacity to assess the comparative risks of medications after they enter the market. For rare adverse events, the pooling of data from multiple sources is necessary to have the power and sufficient population heterogeneity to detect differences in safety and effectiveness in genetic, ethnic and clinically defined subpopulations. However, combining datasets from different data custodians or jurisdictions to perform an analysis on the pooled data creates significant privacy concerns that would need to be addressed. Existing protocols for addressing these concerns can result in reduced analysis accuracy and can allow sensitive information to leak. To develop a secure distributed multi-party computation protocol for logistic regression that provides strong privacy guarantees. We developed a secure distributed logistic regression protocol using a single analysis center with multiple sites providing data. A theoretical security analysis demonstrates that the protocol is robust to plausible collusion attacks and does not allow the parties to gain new information from the data that are exchanged among them. The computational performance and accuracy of the protocol were evaluated on simulated datasets. The computational performance scales linearly as the dataset sizes increase. The addition of sites results in an exponential growth in computation time. However, for up to five sites, the time is still short and would not affect practical applications. The model parameters are the same as the results on pooled raw data analyzed in SAS, demonstrating high model accuracy. The proposed protocol and prototype system would allow the development of logistic regression models in a secure manner without requiring the sharing of personal health information. This can alleviate one of the key barriers to the establishment of large-scale post-marketing surveillance programs. We extended the secure protocol to account for correlations among patients within sites through generalized estimating equations, and to accommodate other link functions by extending it to generalized linear models.

Risk of Resource Failure and Toolkit Variation in Small-Scale Farmers and Herders

PubMed Central

Collard, Mark; Ruttle, April; Buchanan, Briggs; O’Brien, Michael J.

2012-01-01

Recent work suggests that global variation in toolkit structure among hunter-gatherers is driven by risk of resource failure such that as risk of resource failure increases, toolkits become more diverse and complex. Here we report a study in which we investigated whether the toolkits of small-scale farmers and herders are influenced by risk of resource failure in the same way. In the study, we applied simple linear and multiple regression analysis to data from 45 small-scale food-producing groups to test the risk hypothesis. Our results were not consistent with the hypothesis; none of the risk variables we examined had a significant impact on toolkit diversity or on toolkit complexity. It appears, therefore, that the drivers of toolkit structure differ between hunter-gatherers and small-scale food-producers. PMID:22844421

Fear of Death in a Sample of Physicians

PubMed Central

Wood, Keith; Robinson, Paul J.

1984-01-01

Recently, reliable and valid methods of assessing fear of death have been developed. In this study, three well established questionnaires (the Threat Index, the Death Anxiety Scale and the Collett-Lester Fear of Death Scale) were used to assess and compare fear of death in a group of physicians (n = 30) with a group of non-physicians (n = 30). T-tests and hierarchical multiple regression analyses revealed no significant differences between physicians' and non-physicians' fear of death as measured by the Threat Index and Templer's Death Anxiety Scale. The Collett-Lester Fear of Death Scale revealed that physicians were less fearful of death. More specifically, physicians demonstrated less fear on the Collett-Lester subscales, `fear of dying of self' and `fear of dying of others', than did non-physicians. These findings and those of earlier, contradictory research, are discussed. PMID:21279021

An iteratively reweighted least-squares approach to adaptive robust adjustment of parameters in linear regression models with autoregressive and t-distributed deviations

NASA Astrophysics Data System (ADS)

Kargoll, Boris; Omidalizarandi, Mohammad; Loth, Ina; Paffenholz, Jens-André; Alkhatib, Hamza

2018-03-01

In this paper, we investigate a linear regression time series model of possibly outlier-afflicted observations and autocorrelated random deviations. This colored noise is represented by a covariance-stationary autoregressive (AR) process, in which the independent error components follow a scaled (Student's) t-distribution. This error model allows for the stochastic modeling of multiple outliers and for an adaptive robust maximum likelihood (ML) estimation of the unknown regression and AR coefficients, the scale parameter, and the degree of freedom of the t-distribution. This approach is meant to be an extension of known estimators, which tend to focus only on the regression model, or on the AR error model, or on normally distributed errors. For the purpose of ML estimation, we derive an expectation conditional maximization either algorithm, which leads to an easy-to-implement version of iteratively reweighted least squares. The estimation performance of the algorithm is evaluated via Monte Carlo simulations for a Fourier as well as a spline model in connection with AR colored noise models of different orders and with three different sampling distributions generating the white noise components. We apply the algorithm to a vibration dataset recorded by a high-accuracy, single-axis accelerometer, focusing on the evaluation of the estimated AR colored noise model.

The role of social support in anxiety for persons with COPD.

PubMed

Dinicola, Gia; Julian, Laura; Gregorich, Steven E; Blanc, Paul D; Katz, Patricia P

2013-02-01

This study examined the contribution of perceived social support to the presence of anxiety in persons with chronic obstructive pulmonary disease (COPD). A cross-sectional survey sample of 452 persons with COPD (61.3% female; 53.5% older than 65; 70.8% without a college degree or higher educational achievement, and 54.8% with household income of $40,000 or less) completed a telephone survey. Measures included the anxiety subscale of the Hospital Anxiety and Depression Scale (HADS-A), 5 social support subscales from the Positive and Negative Social Exchanges (PANSE) Scale, a COPD Severity Score (CSS; a weighted algorithmic combination of symptoms and the need for various COPD medical interventions), and the Geriatric Depression Scale, Short Form (GDS-SF). Zero order correlations and a series of multiple regression analyses were calculated. Multiple regression analysis revealed that the receipt of instrumental support, feeling let down by the failure of others to provide needed help, and unsympathetic or insensitive behavior from others each positively predicted a higher level of patient anxiety in COPD patients, after controlling for demographic variables, smoking status, comorbid depression (GDS) and severity of illness (CSS). Additionally, the control variable of depression was the strongest predictor of anxiety, suggesting a high degree of co-morbidity in this sample. Anxiety and depression are serious co-morbid mental health concerns for persons with COPD. It is important to examine both positive and negative aspects of perceived social support for COPD patients and how they may impact or interact with these mental health concerns. Copyright © 2012 Elsevier Inc. All rights reserved.

Medication Adherence, Work Performance and Self-Esteem among Psychiatric Patients Attending Psychosocial Rehabilitation Services at Bangalore, India.

PubMed

Gandhi, Sailaxmi; Pavalur, Rajitha; Thanapal, Sivakumar; Parathasarathy, Nirmala B; Desai, Geetha; Bhola, Poornima; Philip, Mariamma; Chaturvedi, Santosh K

2014-10-01

Work benefits mental health in innumerable ways. Vocational rehabilitation can enhance self-esteem. Medication adherence can improve work performance and thereby the individuals' self-esteem. To test the hypothesis that there would be a significant correlation between medication adherence, work performance and self-esteem. A quantitative, descriptive correlational research design was adopted to invite patients attending psychiatric rehabilitation services to participate in the research. Data was collected from a convenience sample of 60 subjects using the 'Medication Adherence Rating scale', 'Griffiths work behaviour scale' and the 'Rosenberg's Self-esteem scale'. Analysis was done using spss18 with descriptive statistics, Pearsons correlation coefficient and multiple regression analysis. There were 36 males and 24 females who participated in this study. The subjects had good mean medication adherence of 8.4 ± 1.5 with median of 9.00, high mean self-esteem of 17.65 ± 2.97 with median of 18.0 and good mean work performance of 88.62 ± 22.56 with median of 93.0. Although weak and not significant, there was a positive correlation (r = 0.22, P = 0.103) between medication adherence and work performance; positive correlation between (r = 0.25, P = 0.067) medication adherence and self-esteem; positive correlation between (r = 0.136, P = 0.299) work performance and self-esteem. Multiple regression analysis showed no significant predictors for medication adherence, work performance and self-esteem among patients with psychiatric illness. Medication monitoring and strengthening of work habit can improve self-esteem thereby, strengthening hope of recovery from illness.

Work Ability Index (WAI) and its health-related determinants among Iranian farmers working in small farm enterprises.

PubMed

Rostamabadi, Akbar; Mazloumi, Adel; Rahimi Foroushani, Abbas

2014-01-01

This study aimed to determine the Work Ability Index (WAI) and examine the influence of health dimensions and demographic variables on the work ability of Iranian farmers working in small farm enterprises. A cross-sectional study was conducted among 294 male farmers. The WAI and SF-36 questionnaires were used to determine work ability and health status. The effect of demographics variables on the work ability index was investigated with the independent samples t-test and one-way ANOVA. Also, multiple linear regression analysis was used to test the association between the mean WAI score and the SF-36 scales. The mean WAI score was 35.1 (SD=10.6). One-way ANOVA revealed a significant relationship between the mean WAI and age. Multiple linear regression analysis showed that work ability was more influenced by physical scales of the health dimensions, such as physical function, role-physical, and general health, whereas a lower association was found for mental scales such as mental health. The average WAI was at a moderate work ability level for the sample population of farmers in this study. Based on the WAI guidelines, improvement of work ability and identification of factors affecting it should be considered a priority in interventional programs. Given the influence of health dimensions on WAI, any intervention program for preservation and promotion of work ability among the studied farmers should be based on balancing and optimizing the physical and psychosocial work environments, with a special focus on reducing physical work load.(J Occup Health 2014; 56: 478-484).

Spatial patterns of air pollutants and social groups: a distributive environmental justice study in the phoenix metropolitan region of USA

NASA Astrophysics Data System (ADS)

Pope, Ronald; Wu, Jianguo; Boone, Christopher

2016-11-01

Quantifying spatial distribution patterns of air pollutants is imperative to understand environmental justice issues. Here we present a landscape-based hierarchical approach in which air pollution variables are regressed against population demographics on multiple spatiotemporal scales. Using this approach, we investigated the potential problem of distributive environmental justice in the Phoenix metropolitan region, focusing on ambient ozone and particulate matter. Pollution surfaces (maps) are evaluated against the demographics of class, age, race (African American, Native American), and ethnicity (Hispanic). A hierarchical multiple regression method is used to detect distributive environmental justice relationships. Our results show that significant relationships exist between the dependent and independent variables, signifying possible environmental inequity. Although changing spatiotemporal scales only altered the overall direction of these relationships in a few instances, it did cause the relationship to become nonsignificant in many cases. Several consistent patterns emerged: people aged 17 and under were significant predictors for ambient ozone and particulate matter, but people 65 and older were only predictors for ambient particulate matter. African Americans were strong predictors for ambient particulate matter, while Native Americans were strong predictors for ambient ozone. Hispanics had a strong negative correlation with ambient ozone, but a less consistent positive relationship with ambient particulate matter. Given the legacy conditions endured by minority racial and ethnic groups, and the relative lack of mobility of all the groups, our findings suggest the existence of environmental inequities in the Phoenix metropolitan region. The methodology developed in this study is generalizable with other pollutants to provide a multi-scaled perspective of environmental justice issues.

Quantile regression and clustering analysis of standardized precipitation index in the Tarim River Basin, Xinjiang, China

NASA Astrophysics Data System (ADS)

Yang, Peng; Xia, Jun; Zhang, Yongyong; Han, Jian; Wu, Xia

2017-11-01

Because drought is a very common and widespread natural disaster, it has attracted a great deal of academic interest. Based on 12-month time scale standardized precipitation indices (SPI12) calculated from precipitation data recorded between 1960 and 2015 at 22 weather stations in the Tarim River Basin (TRB), this study aims to identify the trends of SPI and drought duration, severity, and frequency at various quantiles and to perform cluster analysis of drought events in the TRB. The results indicated that (1) both precipitation and temperature at most stations in the TRB exhibited significant positive trends during 1960-2015; (2) multiple scales of SPIs changed significantly around 1986; (3) based on quantile regression analysis of temporal drought changes, the positive SPI slopes indicated less severe and less frequent droughts at lower quantiles, but clear variation was detected in the drought frequency; and (4) significantly different trends were found in drought frequency probably between severe droughts and drought frequency.

Calibration of an M L scale for South Africa using tectonic earthquake data recorded by the South African National Seismograph Network: 2006 to 2009

NASA Astrophysics Data System (ADS)

Saunders, Ian; Ottemöller, Lars; Brandt, Martin B. C.; Fourie, Christoffel J. S.

2013-04-01

A relation to determine local magnitude ( M L) based on the original Richter definition is empirically derived from synthetic Wood-Anderson seismograms recorded by the South African National Seismograph Network. In total, 263 earthquakes in the distance range 10 to 1,000 km, representing 1,681 trace amplitudes measured in nanometers from synthesized Wood-Anderson records on the vertical channel were considered to derive an attenuation relation appropriate for South Africa through multiple regression analysis. Additionally, station corrections were determined for 26 stations during the regression analysis resulting in values ranging between -0.31 and 0.50. The most appropriate M L scale for South Africa from this study satisfies the equation: {M_{{{L}}}} = {{lo}}{{{g}}_{{10}}}(A) + 1.149{{lo}}{{{g}}_{{10}}}(R) + 0.00063R + 2.04 - S The anelastic attenuation term derived from this study indicates that ground motion attenuation is significantly different from Southern California but comparable with stable continental regions.

War-related trauma exposure and multiple risk behaviors among school-going adolescents in Northern Uganda: the mediating role of depression symptoms.

PubMed

Okello, James; Nakimuli-Mpungu, Etheldreda; Musisi, Seggane; Broekaert, Eric; Derluyn, Ilse

2013-11-01

The relationship between war-related trauma exposure, depressive symptoms and multiple risk behaviors among adolescents is less clear in sub-Saharan Africa. We analyzed data collected from a sample of school-going adolescents four years postwar. Participants completed interviews assessing various risk behaviors defined by the Youth Self Report (YSR) and a sexual risk behavior survey, and were screened for post-traumatic stress, anxiety and depression symptoms based on the Impact of Events Scale Revised (IESR) and Hopkins Symptom Checklist for Adolescents (HSCL-37A) respectively. Multivariate logistic regression was used to assess factors independently associated with multiple risk behaviors. The logistic regression model of Baron and Kenny (1986) was used to evaluate the mediating role of depression in the relationship between stressful war events and multiple risk behaviors. Of 551 participants, 139 (25%) reported multiple (three or more) risk behaviors in the past year. In the multivariate analyses, depression symptoms remained uniquely associated with multiple risk behavior after adjusting for potential confounders including socio-demographic characteristics, war-related trauma exposure variables, anxiety and post-traumatic stress symptoms. In mediation analysis, depression symptoms mediated the associations between stressful war events and multiple risk behaviors. The psychometric properties of the questionnaires used in this study are not well established in war affected African samples thus ethno cultural variation may decrease the validity of our measures. Adolescents with depression may be at a greater risk of increased engagement in multiple risk behaviors. Culturally sensitive and integrated interventions to treat and prevent depression among adolescents in post-conflict settings are urgently needed. © 2013 Elsevier B.V. All rights reserved.

Nepalese undergraduate nursing students' perceptions of the clinical learning environment, supervision and nurse teachers: A questionnaire survey.

PubMed

Nepal, Bijeta; Taketomi, Kikuko; Ito, Yoichi M; Kohanawa, Masashi; Kawabata, Hidenobu; Tanaka, Michiko; Otaki, Junji

2016-04-01

Clinical practice enables nursing students to acquire essential professional skills, but little is known about nursing students' perceptions of the clinical learning environment (CLE) in Nepal. To examine Nepalese nursing students' perceptions regarding the CLE and supervision. A cross-sectional questionnaire design was used. Government and private hospitals in Nepal where the undergraduate nursing college students undertook their clinical practice. Students with clinical practice experience were recruited from years 2-4 of the B.Sc. nursing program in Nepal (n=350). The final sample comprised 263 students. A self-administered questionnaire including demographic characteristics, latest clinical practice site, and general satisfaction was administered February-March 2014. The previously validated Clinical Learning Environment, Supervision and Nurse Teacher evaluation scale was used in the questionnaire. The analytical approach used exploratory factor analysis, assessments of the scale and sub-dimension reliability, correlations of factors between scale sub-dimensions, and multiple regression analysis. Students' practicum satisfaction level at government hospitals was significantly higher than those at private hospitals (p<0.0001). Five factors explained 85.7% of the variance, with minor factorial structure differences compared with the original scale. Reliability was confirmed (Cronbach's alpha=0.93 for total scale, 0.76-0.92 for sub-dimensions). Inter-correlations between the five original sub-dimensions were 0.27-0.68 (p<0.0001). Students undertaking their practicum in private hospitals evaluated their clinical placements significantly more negatively on most sub-dimensions than those in government hospitals. Multiple regression analysis revealed a significant positive relationship between satisfaction and pedagogical atmosphere (p<0.0001). This is the first study to investigate nursing students' perceptions of the CLE in undergraduate nursing programs in Nepal. Students were satisfied with the CLE overall, but satisfaction varied by practicum hospital sector. The most influential factor explaining satisfaction was pedagogical atmosphere. Copyright © 2016 Elsevier Ltd. All rights reserved.

Amount of balance necessary for the independence of transfer and stair-climbing in stroke inpatients.

PubMed

Fujita, Takaaki; Sato, Atsushi; Ohashi, Yuji; Nishiyama, Kazutaka; Ohashi, Takuro; Yamane, Kazuhiro; Yamamoto, Yuichi; Tsuchiya, Kenji; Otsuki, Koji; Tozato, Fusae

2018-05-01

The purpose of this study was to clarify the amount of balance necessary for the independence of transfer and stair-climbing in stroke patients. This study included 111 stroke inpatients. Simple and multiple regression analyses were conducted to establish the association between the FIM ® instrument scores for transfer or stair-climbing and Berg Balance Scale. Furthermore, receiver operating characteristic curves were used to elucidate the amount of balance necessary for the independence of transfer and stair-climbing. Simple and multiple regression analyses showed that the FIM ® instrument scores for transfer and stair-climbing were strongly associated with Berg Balance Scale. On comparison of the independent and supervision-dependent groups, Berg Balance Scale cut-off values for transfer and stair-climbing were 41/40 and 54/53 points, respectively. On comparison of the independent-supervision and dependent groups, the cut-off values for transfer and stair-climbing were 30/29 and 41/40 points, respectively. The calculated cut-off values indicated the amount of balance necessary for the independence of transfer and stair-climbing, with and without supervision, in stroke patients. Berg Balance Scale has a good discriminatory ability and cut-off values are clinically useful to determine the appropriate independence levels of transfer and stair-climbing in hospital wards. Implications for rehabilitation The Berg Balance Scale's (BBS) strong association with transfer and stair-climbing independence and performance indicates that establishing cut-off values is vitally important for the established use of the BBS clinically. The cut-off values calculated herein accurately demonstrate the level of balance necessary for transfer and stair-climbing independence, with and without supervision, in stroke patients. These criteria should be employed clinically for determining the level of independence for transfer and stair-climbing as well as for setting balance training goals aimed at improving transfer and stair-climbing.

Association between overuse of mobile phones on quality of sleep and general health among occupational health and safety students.

PubMed

Eyvazlou, Meysam; Zarei, Esmaeil; Rahimi, Azin; Abazari, Malek

2016-01-01

Concerns about health problems due to the increasing use of mobile phones are growing. Excessive use of mobile phones can affect the quality of sleep as one of the important issues in the health literature and general health of people. Therefore, this study investigated the relationship between the excessive use of mobile phones and general health and quality of sleep on 450 Occupational Health and Safety (OH&S) students in five universities of medical sciences in the North East of Iran in 2014. To achieve this objective, special questionnaires that included Cell Phone Overuse Scale, Pittsburgh's Sleep Quality Index (PSQI) and General Health Questionnaire (GHQ) were used, respectively. In addition to descriptive statistical methods, independent t-test, Pearson correlation, analysis of variance (ANOVA) and multiple regression tests were performed. The results revealed that half of the students had a poor level of sleep quality and most of them were considered unhealthy. The Pearson correlation co-efficient indicated a significant association between the excessive use of mobile phones and the total score of general health and the quality of sleep. In addition, the results of the multiple regression showed that the excessive use of mobile phones has a significant relationship between each of the four subscales of general health and the quality of sleep. Furthermore, the results of the multivariate regression indicated that the quality of sleep has a simultaneous effect on each of the four scales of the general health. Overall, a simultaneous study of the effects of the mobile phones on the quality of sleep and the general health could be considered as a trigger to employ some intervention programs to improve their general health status, quality of sleep and consequently educational performance.

Quality of life of patients who undergo breast reconstruction after mastectomy: effects of personality characteristics.

PubMed

Bellino, Silvio; Fenocchio, Marina; Zizza, Monica; Rocca, Giuseppe; Bogetti, Paolo; Bogetto, Filippo

2011-01-01

Reconstruction after mastectomy has become an integral part of breast cancer treatment. The effects of psychological factors on quality of life after reconstruction have been poorly investigated. The authors examined clinical and personality characteristics related to quality of life in patients receiving reconstructive surgery. All patients received immediate reconstruction and were evaluated in the week before tissue expander implantation (T0) with a semistructured interview for demographic and clinical characteristics, the Temperament and Character Inventory, the Inventory of Interpersonal Problems, the Short Form Health Survey, the Severity Item of the Clinical Global Impression, the Hamilton Depression Rating Scale, and the Hamilton Anxiety Rating Scale. Assessment with the Short Form was repeated 3 months after expander placement (T1). Statistics were calculated with univariate regression and analysis of variance. Significant variables were included in a multiple regression analysis to identify factors related to the change T1-T0 of the mean of the Short Form-transformed scores. Results were significant when p was less than or equal to 0.05. Fifty-seven women were enrolled. Results of multiple regression analysis showed that the Temperament and Character Inventory personality dimension harm avoidance and the Inventory of Interpersonal Problems domain vindictive/self-centered were significantly and independently related to the change in Short Form mean score. Personality dimensions and patterns of interpersonal functioning produce significant effects on patients' quality of life during breast reconstruction. Patients with high harm avoidance are apprehensive and doubtful. Restoration of body image could help them to reduce social anxiety and insecurity. Vindictive/self-centered patients are resentful and aggressive. Breast reconstruction could symbolize the conclusion of a reparative process and fulfill the desire of revenge on cancer.

Bayesian LASSO, scale space and decision making in association genetics.

PubMed

Pasanen, Leena; Holmström, Lasse; Sillanpää, Mikko J

2015-01-01

LASSO is a penalized regression method that facilitates model fitting in situations where there are as many, or even more explanatory variables than observations, and only a few variables are relevant in explaining the data. We focus on the Bayesian version of LASSO and consider four problems that need special attention: (i) controlling false positives, (ii) multiple comparisons, (iii) collinearity among explanatory variables, and (iv) the choice of the tuning parameter that controls the amount of shrinkage and the sparsity of the estimates. The particular application considered is association genetics, where LASSO regression can be used to find links between chromosome locations and phenotypic traits in a biological organism. However, the proposed techniques are relevant also in other contexts where LASSO is used for variable selection. We separate the true associations from false positives using the posterior distribution of the effects (regression coefficients) provided by Bayesian LASSO. We propose to solve the multiple comparisons problem by using simultaneous inference based on the joint posterior distribution of the effects. Bayesian LASSO also tends to distribute an effect among collinear variables, making detection of an association difficult. We propose to solve this problem by considering not only individual effects but also their functionals (i.e. sums and differences). Finally, whereas in Bayesian LASSO the tuning parameter is often regarded as a random variable, we adopt a scale space view and consider a whole range of fixed tuning parameters, instead. The effect estimates and the associated inference are considered for all tuning parameters in the selected range and the results are visualized with color maps that provide useful insights into data and the association problem considered. The methods are illustrated using two sets of artificial data and one real data set, all representing typical settings in association genetics.

Psychological effects of disaster relief activities on Japan ground self-defense force personnel following the 2011 great east Japan earthquake.

PubMed

Dobashi, Kosuke; Nagamine, Masanori; Shigemura, Jun; Tsunoda, Tomoya; Shimizu, Kunio; Yoshino, Aihide; Nomura, Soichiro

2014-01-01

Disaster relief workers are potentially exposed to severe stressors on the job, resulting in a variety of psychological responses. This study aims to clarify the psychological effects of disaster relief activities on Japan Ground Self-Defense Force (JGSDF) personnel following the 2011 Great East Japan Earthquake. A self-report questionnaire was administered to 606 JGSDF personnel one month after completing the disaster relief mission. Posttraumatic stress responses and general psychological distress were assessed using the Impact of Event Scale-Revised (IES-R) and the K10 scales. Associations between outcome variables and independent variables (age, gender, military rank, length of deployment, and exposure to dead bodies) were measured with univariate analyses and subsequent multiple logistic regression analyses. The mean (± SD) IES-R score was 6.2 (± 8.1), and the mean K10 score was 12.8 (± 4.4). In the univariate analyses, exposure to dead bodies and age were identified as significant factors for IES-R and K10 scores, (p < 0.01). However, the multiple logistic regression analyses did not reveal any significant factors although body handlers' exposure approached significance for IES-R. The subjects reported very low psychological responses despite the severe nature of their disaster relief activities. Several factors may account for the low levels of psychological distress and posttraumatic symptoms observed in this study.

Role of Alexithymia, Anxiety, and Depression in Predicting Self-Efficacy in Academic Students

PubMed Central

2017-01-01

Objective. Little research is available on the predictive factors of self-efficacy in college students. The aim of the present study is to examine the role of alexithymia, anxiety, and depression in predicting self-efficacy in academic students. Design. In a cross-sectional study, a total of 133 students at Babol University of Medical Sciences (Medicine, Dentistry, and Paramedicine) participated in the study between 2014 and 2015. All participants completed the Toronto Alexithymia Scale (TAS-20), College Academic Self-Efficacy Scale (CASES), and 14 items on anxiety and depression derived from the 28 items of the General Health Questionnaire (28-GHQ). Results. Pearson correlation coefficients revealed negative significant relationships between alexithymia and the three subscales with student self-efficacy. There was no significant correlation between anxiety/depression symptoms and student self-efficacy. A backward multiple regression analysis revealed that alexithymia was a negative significant predictor of self-efficacy in academic students (B = −0.512, P < 0.001). The prevalence of alexithymia was 21.8% in students. Multiple backward logistic analysis regression revealed that number of passed semesters, gender, mother's education, father's education, and doctoral level did not accurately predict alexithymia in college students. Conclusion. As alexithymia is prevalent in college students and affects self-efficacy and academic functioning, we suggest it should be routinely evaluated by mental physicians at universities. PMID:28154839

Associations of health behaviors on depressive symptoms among employed men in Japan.

PubMed

Wada, Koji; Satoh, Toshihiko; Tsunoda, Masashi; Aizawa, Yoshiharu

2006-07-01

The associations between health behaviors and depressive symptoms have been demonstrated in many studies. However, job strain has also been associated with health behaviors. The aim of this study was to analyze whether health behaviors such as physical activity, sleeping, smoking and alcohol intake are associated with depressive symptoms after adjusting for job strain. Workers were recruited from nine companies and factories located in east and central areas of Japan. The Center for Epidemiologic Studies Depression (CES-D) Scale was used to assess depressive symptoms. Psychological demand and control (decision-latitude) at work were measured with the Job Content Questionnaire. Multiple logistic regression analysis was used to determine the independent contribution of each health behavior to depressive symptoms. Among the total participants, 3,748 (22.7%) had depressive symptoms, which was defined as scoring 16 or higher on the CES-D scale. Using the multiple logistic regression analysis, depressive symptoms were significantly associated with physical activity less than once a week (adjusted relative risk [ARR] = 1.18, 95% confidence interval [CI], 1.14 to 1.25) and daily hours of sleep of 6 h or less (ARR, 1.25; 95% CI, 1.14 to 1.35). Smoking and frequency of alcohol intake were not significantly associated with depressive symptoms. This study suggests some health behaviors such as physical activity or daily hours of sleep are associated with depressive symptoms after adjusting for job strain.

Predictors for living at home after geriatric inpatient rehabilitation: A prospective cohort study.

PubMed

Kool, Jan; Oesch, Peter; Bachmann, Stefan

2017-01-31

To evaluate patient characteristics predicting living at home after geriatric rehabilitation. Prospective cohort study. A total of 210 patients aged 65 years or older receiving inpatient rehabilitation. Candidate predictors evaluated during rehabilitation were: age, vulnerability (Vulnerable Elders Survey), multimorbidity (Cumulative Illness Rating Scale), cognition (Mini-Mental State Examination), depression (Hospital Anxiety and Depression Scale), living alone, previous independence in activities of daily living, fall risk, and mobility at discharge (Timed Up and Go test). Multiple imputation data-sets, bivariate and multiple regression were used to build a predictive model for living at home, which was evaluated at 3-month follow-up. A total of 210 patients (mean age 76.0 years, 46.2% women) were included in the study. Of these, 87.6% had been admitted to geriatric rehabilitation directly from acute hospital care. Follow-up was complete in 75.2% of patients. The strongest predictor for living at home was better mobility at discharge (Timed Up and Go test < 20 s), followed by lower multimorbidity, better cognition, and not living alone. In bivariate regression, living at home was also associated with age, fall risk, vulnerability, depression, and previous independence in activities of daily living. Mobility is the most important predictive factor for living at home after geriatric rehabilitation. Assessment and training of mobility are therefore key aspects in geriatric rehabilitation.

Role of Alexithymia, Anxiety, and Depression in Predicting Self-Efficacy in Academic Students.

PubMed

Faramarzi, Mahbobeh; Khafri, Soraya

2017-01-01

Objective . Little research is available on the predictive factors of self-efficacy in college students. The aim of the present study is to examine the role of alexithymia, anxiety, and depression in predicting self-efficacy in academic students. Design . In a cross-sectional study, a total of 133 students at Babol University of Medical Sciences (Medicine, Dentistry, and Paramedicine) participated in the study between 2014 and 2015. All participants completed the Toronto Alexithymia Scale (TAS-20), College Academic Self-Efficacy Scale (CASES), and 14 items on anxiety and depression derived from the 28 items of the General Health Questionnaire (28-GHQ). Results . Pearson correlation coefficients revealed negative significant relationships between alexithymia and the three subscales with student self-efficacy. There was no significant correlation between anxiety/depression symptoms and student self-efficacy. A backward multiple regression analysis revealed that alexithymia was a negative significant predictor of self-efficacy in academic students ( B = -0.512, P < 0.001). The prevalence of alexithymia was 21.8% in students. Multiple backward logistic analysis regression revealed that number of passed semesters, gender, mother's education, father's education, and doctoral level did not accurately predict alexithymia in college students. Conclusion . As alexithymia is prevalent in college students and affects self-efficacy and academic functioning, we suggest it should be routinely evaluated by mental physicians at universities.

The role of enamel thickness and refractive index on human tooth colour.

PubMed

Oguro, Rena; Nakajima, Masatoshi; Seki, Naoko; Sadr, Alireza; Tagami, Junji; Sumi, Yasunori

2016-08-01

To investigate the role of enamel thickness and refractive index (n) on tooth colour. The colour and enamel thickness of fifteen extracted human central incisors were determined according to CIELab colour scale using spectrophotometer (Crystaleye) and swept-source optical coherence tomography (SS-OCT), respectively. Subsequently, labial enamel was trimmed by approximately 100μm, and the colour and remaining enamel thickness were investigated again. This cycle was repeated until dentin appeared. Enamel blocks were prepared from the same teeth and their n were obtained using SS-OCT. Multiple regression analysis was performed to reveal any effects of enamel thickness and n on colour difference (ΔE00) and differences in colour parameters with CIELCh and CIELab colour scales. Multiple regression analysis revealed that enamel thickness (p=0.02) and n of enamel (p<0.001) were statistically significant predictors of ΔE00 after complete enamel trimming. The n was also a significant predictor of ΔH' (p=0.01). Enamel thickness and n were not statistically significant predictors of ΔL', ΔC', Δa* and Δb*. Enamel affected tooth colour, in which n was a statistically significant predictor for tooth colour change. Understanding the role of enamel in tooth colour could contribute to development of aesthetic restorative materials that mimic the colour of natural tooth with minimal reduction of the existing enamel. Copyright © 2016 Elsevier Ltd. All rights reserved.

Prediction of hearing outcomes by multiple regression analysis in patients with idiopathic sudden sensorineural hearing loss.

PubMed

Suzuki, Hideaki; Tabata, Takahisa; Koizumi, Hiroki; Hohchi, Nobusuke; Takeuchi, Shoko; Kitamura, Takuro; Fujino, Yoshihisa; Ohbuchi, Toyoaki

2014-12-01

This study aimed to create a multiple regression model for predicting hearing outcomes of idiopathic sudden sensorineural hearing loss (ISSNHL). The participants were 205 consecutive patients (205 ears) with ISSNHL (hearing level ≥ 40 dB, interval between onset and treatment ≤ 30 days). They received systemic steroid administration combined with intratympanic steroid injection. Data were examined by simple and multiple regression analyses. Three hearing indices (percentage hearing improvement, hearing gain, and posttreatment hearing level [HLpost]) and 7 prognostic factors (age, days from onset to treatment, initial hearing level, initial hearing level at low frequencies, initial hearing level at high frequencies, presence of vertigo, and contralateral hearing level) were included in the multiple regression analysis as dependent and explanatory variables, respectively. In the simple regression analysis, the percentage hearing improvement, hearing gain, and HLpost showed significant correlation with 2, 5, and 6 of the 7 prognostic factors, respectively. The multiple correlation coefficients were 0.396, 0.503, and 0.714 for the percentage hearing improvement, hearing gain, and HLpost, respectively. Predicted values of HLpost calculated by the multiple regression equation were reliable with 70% probability with a 40-dB-width prediction interval. Prediction of HLpost by the multiple regression model may be useful to estimate the hearing prognosis of ISSNHL. © The Author(s) 2014.

The relationship between severity of violence in the home and dating violence.

PubMed

Sims, Eva Nowakowski; Dodd, Virginia J Noland; Tejeda, Manuel J

2008-01-01

This study used propositions from the social learning theory to explore the effects of the combined influences of child maltreatment, childhood witness to parental violence, sibling violence, and gender on dating violence perpetration using a modified version of the Conflict Tactics Scale 2 (CTS2). A weighted scoring method was utilized to determine how severity of violence in the home impacts dating violence perpetration. Bivariate correlations and linear regression models indicate significant associations between child maltreatment, sibling violence perpetration, childhood witness to parental violence, gender, and subsequent dating violence perpetration. Multiple regression analyses indicate that for men, history of severe violence victimization (i.e., child maltreatment and childhood witness to parental violence) and severe perpetration (sibling violence) significantly predict dating violence perpetration.

Development of a mobbing short scale in the Gutenberg Health Study.

PubMed

Garthus-Niegel, Susan; Nübling, Matthias; Letzel, Stephan; Hegewald, Janice; Wagner, Mandy; Wild, Philipp S; Blettner, Maria; Zwiener, Isabella; Latza, Ute; Jankowiak, Sylvia; Liebers, Falk; Seidler, Andreas

2016-01-01

Despite its highly detrimental potential, most standard questionnaires assessing psychosocial stress at work do not include mobbing as a risk factor. In the German standard version of COPSOQ, mobbing is assessed with a single item. In the Gutenberg Health Study, this version was used together with a newly developed short scale based on the Leymann Inventory of Psychological Terror. The purpose of the present study was to evaluate the psychometric properties of these two measures, to compare them and to test their differential impact on relevant outcome parameters. This analysis is based on a population-based sample of 1441 employees participating in the Gutenberg Health Study. Exploratory and confirmatory factor analyses and reliability analyses were used to assess the mobbing scale. To determine their predictive validities, multiple linear regression analyses with six outcome parameters and log-binomial regression models for two of the outcome aspects were run. Factor analyses of the five-item scale confirmed a one-factor solution, reliability was α = 0.65. Both the single-item and the five-item scales were associated with all six outcome scales. Effect sizes were similar for both mobbing measures. Mobbing is an important risk factor for health-related outcomes. For the purpose of psychosocial risk assessment in the workplace, both the single-item and the five-item constructs were psychometrically appropriate. Associations with outcomes were about equivalent. However, the single item has the advantage of parsimony, whereas the five-item construct depicts several distinct forms of mobbing.

Investigation of marital satisfaction and its relationship with job stress and general health of nurses in Qazvin, Iran.

PubMed

Azimian, Jalil; Piran, Pegah; Jahanihashemi, Hassan; Dehghankar, Leila

2017-04-01

Pressures in nursing can affect family life and marital problems, disrupt common social problems, increase work-family conflicts and endanger people's general health. To determine marital satisfaction and its relationship with job stress and general health of nurses. This descriptive and cross-sectional study was done in 2015 in medical educational centers of Qazvin by using an ENRICH marital satisfaction scale and General Health and Job Stress questionnaires completed by 123 nurses. Analysis was done by SPSS version 19 using descriptive and analytical statistics (Pearson correlation, t-test, ANOVA, Chi-square, regression line, multiple regression analysis). The findings showed that 64.4% of nurses had marital satisfaction. There was significant relationship between age (p=0.03), job experience (p=0.01), age of spouse (p=0.01) and marital satisfaction. The results showed that there was a significant relationship between marital satisfaction and general health (p<0.0001). Multiple regression analysis showed that there was a significant relationship between depression (p=0.012) and anxiety (p=0.001) with marital satisfaction. Due to high levels of job stress and disorder in general health of nurses and low marital satisfaction by running health promotion programs and paying attention to its dimensions can help work and family health of nurses.

False Positives in Multiple Regression: Unanticipated Consequences of Measurement Error in the Predictor Variables

ERIC Educational Resources Information Center

Shear, Benjamin R.; Zumbo, Bruno D.

2013-01-01

Type I error rates in multiple regression, and hence the chance for false positive research findings, can be drastically inflated when multiple regression models are used to analyze data that contain random measurement error. This article shows the potential for inflated Type I error rates in commonly encountered scenarios and provides new…

Using Robust Standard Errors to Combine Multiple Regression Estimates with Meta-Analysis

ERIC Educational Resources Information Center

Williams, Ryan T.

2012-01-01

Combining multiple regression estimates with meta-analysis has continued to be a difficult task. A variety of methods have been proposed and used to combine multiple regression slope estimates with meta-analysis, however, most of these methods have serious methodological and practical limitations. The purpose of this study was to explore the use…

Use of Multiple Regression and Use-Availability Analyses in Determining Habitat Selection by Gray Squirrels (Sciurus Carolinensis)

Treesearch

John W. Edwards; Susan C. Loeb; David C. Guynn

1994-01-01

Multiple regression and use-availability analyses are two methods for examining habitat selection. Use-availability analysis is commonly used to evaluate macrohabitat selection whereas multiple regression analysis can be used to determine microhabitat selection. We compared these techniques using behavioral observations (n = 5534) and telemetry locations (n = 2089) of...

In situ Raman spectroscopy for simultaneous monitoring of multiple process parameters in mammalian cell culture bioreactors.

PubMed

Whelan, Jessica; Craven, Stephen; Glennon, Brian

2012-01-01

In this study, the application of Raman spectroscopy to the simultaneous quantitative determination of glucose, glutamine, lactate, ammonia, glutamate, total cell density (TCD), and viable cell density (VCD) in a CHO fed-batch process was demonstrated in situ in 3 L and 15 L bioreactors. Spectral preprocessing and partial least squares (PLS) regression were used to correlate spectral data with off-line reference data. Separate PLS calibration models were developed for each analyte at the 3 L laboratory bioreactor scale before assessing its transferability to the same bioprocess conducted at the 15 L pilot scale. PLS calibration models were successfully developed for all analytes bar VCD and transferred to the 15 L scale. Copyright © 2012 American Institute of Chemical Engineers (AIChE).

Building Regression Models: The Importance of Graphics.

ERIC Educational Resources Information Center

Dunn, Richard

1989-01-01

Points out reasons for using graphical methods to teach simple and multiple regression analysis. Argues that a graphically oriented approach has considerable pedagogic advantages in the exposition of simple and multiple regression. Shows that graphical methods may play a central role in the process of building regression models. (Author/LS)

Testing Different Model Building Procedures Using Multiple Regression.

ERIC Educational Resources Information Center

Thayer, Jerome D.

The stepwise regression method of selecting predictors for computer assisted multiple regression analysis was compared with forward, backward, and best subsets regression, using 16 data sets. The results indicated the stepwise method was preferred because of its practical nature, when the models chosen by different selection methods were similar…

Decreasing Multicollinearity: A Method for Models with Multiplicative Functions.

ERIC Educational Resources Information Center

Smith, Kent W.; Sasaki, M. S.

1979-01-01

A method is proposed for overcoming the problem of multicollinearity in multiple regression equations where multiplicative independent terms are entered. The method is not a ridge regression solution. (JKS)

Multiple-Instance Regression with Structured Data

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri L.; Lane, Terran; Roper, Alex

2008-01-01

We present a multiple-instance regression algorithm that models internal bag structure to identify the items most relevant to the bag labels. Multiple-instance regression (MIR) operates on a set of bags with real-valued labels, each containing a set of unlabeled items, in which the relevance of each item to its bag label is unknown. The goal is to predict the labels of new bags from their contents. Unlike previous MIR methods, MI-ClusterRegress can operate on bags that are structured in that they contain items drawn from a number of distinct (but unknown) distributions. MI-ClusterRegress simultaneously learns a model of the bag's internal structure, the relevance of each item, and a regression model that accurately predicts labels for new bags. We evaluated this approach on the challenging MIR problem of crop yield prediction from remote sensing data. MI-ClusterRegress provided predictions that were more accurate than those obtained with non-multiple-instance approaches or MIR methods that do not model the bag structure.

Influence of landscape-scale factors in limiting brook trout populations in Pennsylvania streams

USGS Publications Warehouse

Kocovsky, P.M.; Carline, R.F.

2006-01-01

Landscapes influence the capacity of streams to produce trout through their effect on water chemistry and other factors at the reach scale. Trout abundance also fluctuates over time; thus, to thoroughly understand how spatial factors at landscape scales affect trout populations, one must assess the changes in populations over time to provide a context for interpreting the importance of spatial factors. We used data from the Pennsylvania Fish and Boat Commission's fisheries management database to investigate spatial factors that affect the capacity of streams to support brook trout Salvelinus fontinalis and to provide models useful for their management. We assessed the relative importance of spatial and temporal variation by calculating variance components and comparing relative standard errors for spatial and temporal variation. We used binary logistic regression to predict the presence of harvestable-length brook trout and multiple linear regression to assess the mechanistic links between landscapes and trout populations and to predict population density. The variance in trout density among streams was equal to or greater than the temporal variation for several streams, indicating that differences among sites affect population density. Logistic regression models correctly predicted the absence of harvestable-length brook trout in 60% of validation samples. The r 2-value for the linear regression model predicting density was 0.3, indicating low predictive ability. Both logistic and linear regression models supported buffering capacity against acid episodes as an important mechanistic link between landscapes and trout populations. Although our models fail to predict trout densities precisely, their success at elucidating the mechanistic links between landscapes and trout populations, in concert with the importance of spatial variation, increases our understanding of factors affecting brook trout abundance and will help managers and private groups to protect and enhance populations of wild brook trout. ?? Copyright by the American Fisheries Society 2006.

Impulsivity, self-control, and hypnotic suggestibility.

PubMed

Ludwig, V U; Stelzel, C; Krutiak, H; Prunkl, C E; Steimke, R; Paschke, L M; Kathmann, N; Walter, H

2013-06-01

Hypnotic responding might be due to attenuated frontal lobe functioning after the hypnotic induction. Little is known about whether personality traits linked with frontal functioning are associated with responsiveness to hypnotic suggestions. We assessed whether hypnotic suggestibility is related to the traits of self-control and impulsivity in 154 participants who completed the Brief Self-Control Scale, the Self-Regulation Scale, the Barratt Impulsiveness Scale (BIS-11), and the Harvard Group Scale of Hypnotic Susceptibility (HGSHS:A). BIS-11 non-planning impulsivity correlated positively with HGSHS:A (Bonferroni-corrected). Furthermore, in the best model emerging from a stepwise multiple regression, both non-planning impulsivity and self-control positively predicted hypnotic suggestibility, and there was an interaction of BIS-11 motor impulsivity with gender. For men only, motor impulsivity tended to predict hypnotic suggestibility. Hypnotic suggestibility is associated with personality traits linked with frontal functioning, and hypnotic responding in men and women might differ. Copyright © 2013 Elsevier Inc. All rights reserved.

Core OCD Symptoms: Exploration of Specificity and Relations with Psychopathology

PubMed Central

Stasik, Sara M.; Naragon-Gainey, Kristin; Chmielewski, Michael; Watson, David

2012-01-01

Obsessive-compulsive disorder (OCD) is a heterogeneous condition, comprised of multiple symptom domains. This study used aggregate composite scales representing three core OCD dimensions (Checking, Cleaning, Rituals), as well as Hoarding, to examine the discriminant validity, diagnostic specificity, and predictive ability of OCD symptom scales. The core OCD scales demonstrated strong patterns of convergent and discriminant validity – suggesting that these dimensions are distinct from other self-reported symptoms – whereas hoarding symptoms correlated just as strongly with OCD and non-OCD symptoms in most analyses. Across analyses, our results indicated that Checking is a particularly strong, specific marker of OCD diagnosis, whereas the specificity of Cleaning and Hoarding to OCD was less strong. Finally, the OCD Checking scale was the only significant predictor of OCD diagnosis in logistic regression analyses. Results are discussed with regard to the importance of assessing OCD symptom dimensions separately and implications for classification. PMID:23026094

Clinical Value of Dorsal Medulla Oblongata Involvement Detected with Conventional MRI for Prediction of Outcome in Children with Enterovirus 71-related Brainstem Encephalitis.

PubMed

Liu, Kun; Zhou, Yongjin; Cui, Shihan; Song, Jiawen; Ye, Peipei; Xiang, Wei; Huang, Xiaoyan; Chen, Yiping; Yan, Zhihan; Ye, Xinjian

2018-04-05

Brainstem encephalitis is the most common neurologic complication after enterovirus 71 infection. The involvement of brainstem, especially the dorsal medulla oblongata, can cause severe sequelae or death in children with enterovirus 71 infection. We aimed to determine the prevalence of dorsal medulla oblongata involvement in children with enterovirus 71-related brainstem encephalitis (EBE) by using conventional MRI and to evaluate the value of dorsal medulla oblongata involvement in outcome prediction. 46 children with EBE were enrolled in the study. All subjects underwent a 1.5 Tesla MR examination of the brain. The disease distribution and clinical data were collected. Dichotomized outcomes (good versus poor) at longer than 6 months were available for 28 patients. Logistic regression was used to determine whether the MRI-confirmed dorsal medulla oblongata involvement resulted in improved clinical outcome prediction when compared with other location involvement. Of the 46 patients, 35 had MRI evidence of dorsal medulla oblongata involvement, 32 had pons involvement, 10 had midbrain involvement, and 7 had dentate nuclei involvement. Patients with dorsal medulla oblongata involvement or multiple area involvement were significantly more often in the poor outcome group than in the good outcome group. Logistic regression analysis showed that dorsal medulla oblongata involvement was the most significant single variable in outcome prediction (predictive accuracy, 90.5%), followed by multiple area involvement, age, and initial glasgow coma scale score. Dorsal medulla oblongata involvement on conventional MRI correlated significantly with poor outcomes in EBE children, improved outcome prediction when compared with other clinical and disease location variables, and was most predictive when combined with multiple area involvement, glasgow coma scale score and age.

Evaluation of the laboratory mouse model for screening topical mosquito repellents.

PubMed

Rutledge, L C; Gupta, R K; Wirtz, R A; Buescher, M D

1994-12-01

Eight commercial repellents were tested against Aedes aegypti 0 and 4 h after application in serial dilution to volunteers and laboratory mice. Results were analyzed by multiple regression of percentage of biting (probit scale) on dose (logarithmic scale) and time. Empirical correction terms for conversion of values obtained in tests on mice to values expected in tests on human volunteers were calculated from data obtained on 4 repellents and evaluated with data obtained on 4 others. Corrected values from tests on mice did not differ significantly from values obtained in tests on volunteers. Test materials used in the study were dimethyl phthalate, butopyronoxyl, butoxy polypropylene glycol, MGK Repellent 11, deet, ethyl hexanediol, Citronyl, and dibutyl phthalate.

Parenting styles and alcohol consumption among Brazilian adolescents.

PubMed

Paiva, Fernando Santana; Bastos, Ronaldo Rocha; Ronzani, Telmo Mota

2012-10-01

This study evaluates the correlation between alcohol consumption in adolescence and parenting styles of socialization among Brazilian adolescents. The sample was composed of 273 adolescents, 58% whom were males. Instruments were: 1) Sociodemographic Questionnaire; 2) Demand and Responsiveness Scales; 3) Drug Use Screening Inventory (DUSI). Study analyses employed multiple correspondence analysis and logistic regression. Maternal, but not paternal, authoritative and authoritarian parenting styles were directly related to adolescent alcohol intake. The style that mothers use to interact with their children may influence uptake of high-risk behaviors.

The DSM-5 alternative model of personality disorders from the perspective of adult attachment: a study in community-dwelling adults.

PubMed

Fossati, Andrea; Krueger, Robert F; Markon, Kristian E; Borroni, Serena; Maffei, Cesare; Somma, Antonella

2015-04-01

To assess how the maladaptive personality domains and facets that were included in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) Alternative Model of Personality Disorders relate to adult attachment styles, 480 Italian nonclinical adults were administered the Personality Inventory for DSM-5 (PID-5) and the Attachment Style Questionnaire (ASQ). To evaluate the uniqueness of the associations between the PID-5 scales and the ASQ scales, the participants were also administered the Big Five Inventory (BFI). Multiple regression analyses showed that the ASQ scales significantly predicted both PID-5 domain scales and BFI scales; however, the relationships were different both qualitatively and quantitatively. With the exception of the PID-5 risk taking scale (adjusted R(2) = 0.02), all other PID-5 trait scales were significantly predicted by the ASQ scales, median adjusted R(2) value = 0.25, all ps < 0.001. Our findings suggest that the maladaptive personality domains and traits listed in the DSM-5 Alternative Model of Personality Disorders show meaningful associations with adult attachment styles.

The relationship between spiritual well-being and health-related quality of life in college students.

PubMed

Anye, Ernest Tamanji; Gallien, Tara L; Bian, Hui; Moulton, Michael

2013-01-01

This study investigated the relationship between spiritual well-being (SWB) and various aspects of health-related quality of life (HRQL) of college students. Two hundred twenty-five participants were surveyed during October 2010 to assess SWB and HRQL using the Spiritual Well-Being Scale and questions from the Centers for Disease Control and Prevention's scale for HRQL, respectively. Hierarchical multiple linear regression analyses tested the relationship between SWB and multiple measures of HRQL while controlling for sex, age, and race. Participants who reported higher SWB scores were more likely to participate in religious-type activities and report better HRQL compared with students who reported a moderate sense of SWB. Jointly, SWB and participation in religious activities explained 18% of the variance in HQRL in this sample. SWB made a significant contribution to HRQL in a sample of college students. Such a relationship should be considered by campus health program planners to improve the quality of life of young adults.

Impact of Depression, Fatigue, and Global Measure of Cortical Volume on Cognitive Impairment in Multiple Sclerosis

PubMed Central

De Cola, Maria Cristina; D'Aleo, Giangaetano; Sessa, Edoardo; Marino, Silvia

2015-01-01

Objective. To investigate the influence of demographic and clinical variables, such as depression, fatigue, and quantitative MRI marker on cognitive performances in a sample of patients affected by multiple sclerosis (MS). Methods. 60 MS patients (52 relapsing remitting and 8 primary progressive) underwent neuropsychological assessments using Rao's Brief Repeatable Battery of Neuropsychological Tests (BRB-N), the Beck Depression Inventory-second edition (BDI-II), and the Fatigue Severity Scale (FSS). We performed magnetic resonance imaging to all subjects using a 3 T scanner and obtained tissue-specific volumes (normalized brain volume and cortical brain volume). We used Student's t-test to compare depressed and nondepressed MS patients. Finally, we performed a multivariate regression analysis in order to assess possible predictors of patients' cognitive outcome among demographic and clinical variables. Results. 27.12% of the sample (16/59) was cognitively impaired, especially in tasks requiring attention and information processing speed. From between group comparison, we find that depressed patients had worse performances on BRB-N score, greater disability and disease duration, and brain volume decrease. According to multiple regression analysis, the BDI-II score was a significant predictor for most of the neuropsychological tests. Conclusions. Our findings suggest that the presence of depressive symptoms is an important determinant of cognitive performance in MS patients. PMID:25861633

Crude oil price forecasting based on hybridizing wavelet multiple linear regression model, particle swarm optimization techniques, and principal component analysis.

PubMed

Shabri, Ani; Samsudin, Ruhaidah

2014-01-01

Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series.

A cross-sectional study for estimation of associations between education level and osteoporosis in a Chinese men sample.

PubMed

Yu, Cai-Xia; Zhang, Xiu-Zhen; Zhang, Keqin; Tang, Zihui

2015-12-09

The main aim of this study was to evaluate the association between education level and osteoporosis (OP) in general Chinese Men. We conducted a large-scale, community-based, cross-sectional study to investigate the association by using self-report questionnaire to assess education levels. The data of 1092 men were available for analysis in this study. Multiple regression models controlling for confounding factors to include education level were performed to explore the relationship between education level and OP. Positive correlations between education level and T-score of quantitative bone ultrasound (QUS-T score) were reported (β = 0.108, P value < 0.001). Multiple regression analysis indicated that the education level was independently and significantly associated with OP (P < 0.1 for all models). The men with lower education level had a higher prevalence of OP. The education level was independently and significantly associated with OP. The prevalence of OP was more frequent in Chinese men with lower education level. ClinicalTrials.gov Identifier: NCT02451397 ; date of registration: 05/28/2015).

Crude Oil Price Forecasting Based on Hybridizing Wavelet Multiple Linear Regression Model, Particle Swarm Optimization Techniques, and Principal Component Analysis

PubMed Central

Shabri, Ani; Samsudin, Ruhaidah

2014-01-01

Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series. PMID:24895666

Real-Time Assessment of Fatigue in Patients With Multiple Sclerosis: How Does It Relate to Commonly Used Self-Report Fatigue Questionnaires?

PubMed

Heine, Martin; van den Akker, Lizanne Eva; Blikman, Lyan; Hoekstra, Trynke; van Munster, Erik; Verschuren, Olaf; Visser-Meily, Anne; Kwakkel, Gert

2016-11-01

(1) To assess real-time patterns of fatigue; (2) to assess the association between a real-time fatigue score and 3 commonly used questionnaires (Checklist Individual Strength [CIS] fatigue subscale, Modified Fatigue Impact Scale (MFIS), and Fatigue Severity Scale [FSS]); and (3) to establish factors that confound the association between the real-time fatigue score and the conventional fatigue questionnaires in patients with multiple sclerosis (MS). Cross-sectional study. MS-specialized outpatient facility. Ambulant patients with MS (N=165) experiencing severe self-reported fatigue. Not applicable. A real-time fatigue score was assessed by sending participants 4 text messages on a particular day (How fatigued do you feel at this moment?; score range, 0-10). Latent class growth mixed modeling was used to determine diurnal patterns of fatigue. Regression analyses were used to assess the association between the mean real-time fatigue score and the CIS fatigue subscale, MFIS, and FSS. Significant associations were tested for candidate confounders (eg, disease severity, work status, sleepiness). Four significantly different fatigue profiles were identified by the real-time fatigue score, namely a stable high (n=79), increasing (n=57), stable low (n=16), and decreasing (n=13). The conventional questionnaires correlated poorly (r<.300) with the real-time fatigue score. The Epworth Sleepiness Scale significantly reduced the regression coefficient between the real-time fatigue score and conventional questionnaires, ranging from 15.4% to 35%. Perceived fatigue showed 4 different diurnal patterns in patients with MS. Severity of sleepiness is an important confounder to take into account in the assessment of fatigue. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Accurate age estimation in small-scale societies

PubMed Central

Smith, Daniel; Gerbault, Pascale; Dyble, Mark; Migliano, Andrea Bamberg; Thomas, Mark G.

2017-01-01

Precise estimation of age is essential in evolutionary anthropology, especially to infer population age structures and understand the evolution of human life history diversity. However, in small-scale societies, such as hunter-gatherer populations, time is often not referred to in calendar years, and accurate age estimation remains a challenge. We address this issue by proposing a Bayesian approach that accounts for age uncertainty inherent to fieldwork data. We developed a Gibbs sampling Markov chain Monte Carlo algorithm that produces posterior distributions of ages for each individual, based on a ranking order of individuals from youngest to oldest and age ranges for each individual. We first validate our method on 65 Agta foragers from the Philippines with known ages, and show that our method generates age estimations that are superior to previously published regression-based approaches. We then use data on 587 Agta collected during recent fieldwork to demonstrate how multiple partial age ranks coming from multiple camps of hunter-gatherers can be integrated. Finally, we exemplify how the distributions generated by our method can be used to estimate important demographic parameters in small-scale societies: here, age-specific fertility patterns. Our flexible Bayesian approach will be especially useful to improve cross-cultural life history datasets for small-scale societies for which reliable age records are difficult to acquire. PMID:28696282

Accurate age estimation in small-scale societies.

PubMed

Diekmann, Yoan; Smith, Daniel; Gerbault, Pascale; Dyble, Mark; Page, Abigail E; Chaudhary, Nikhil; Migliano, Andrea Bamberg; Thomas, Mark G

2017-08-01

Precise estimation of age is essential in evolutionary anthropology, especially to infer population age structures and understand the evolution of human life history diversity. However, in small-scale societies, such as hunter-gatherer populations, time is often not referred to in calendar years, and accurate age estimation remains a challenge. We address this issue by proposing a Bayesian approach that accounts for age uncertainty inherent to fieldwork data. We developed a Gibbs sampling Markov chain Monte Carlo algorithm that produces posterior distributions of ages for each individual, based on a ranking order of individuals from youngest to oldest and age ranges for each individual. We first validate our method on 65 Agta foragers from the Philippines with known ages, and show that our method generates age estimations that are superior to previously published regression-based approaches. We then use data on 587 Agta collected during recent fieldwork to demonstrate how multiple partial age ranks coming from multiple camps of hunter-gatherers can be integrated. Finally, we exemplify how the distributions generated by our method can be used to estimate important demographic parameters in small-scale societies: here, age-specific fertility patterns. Our flexible Bayesian approach will be especially useful to improve cross-cultural life history datasets for small-scale societies for which reliable age records are difficult to acquire.

An operational ensemble prediction system for catchment rainfall over eastern Africa spanning multiple temporal and spatial scales

NASA Astrophysics Data System (ADS)

Riddle, E. E.; Hopson, T. M.; Gebremichael, M.; Boehnert, J.; Broman, D.; Sampson, K. M.; Rostkier-Edelstein, D.; Collins, D. C.; Harshadeep, N. R.; Burke, E.; Havens, K.

2017-12-01

While it is not yet certain how precipitation patterns will change over Africa in the future, it is clear that effectively managing the available water resources is going to be crucial in order to mitigate the effects of water shortages and floods that are likely to occur in a changing climate. One component of effective water management is the availability of state-of-the-art and easy to use rainfall forecasts across multiple spatial and temporal scales. We present a web-based system for displaying and disseminating ensemble forecast and observed precipitation data over central and eastern Africa. The system provides multi-model rainfall forecasts integrated to relevant hydrological catchments for timescales ranging from one day to three months. A zoom-in features is available to access high resolution forecasts for small-scale catchments. Time series plots and data downloads with forecasts, recent rainfall observations and climatological data are available by clicking on individual catchments. The forecasts are calibrated using a quantile regression technique and an optimal multi-model forecast is provided at each timescale. The forecast skill at the various spatial and temporal scales will discussed, as will current applications of this tool for managing water resources in Sudan and optimizing hydropower operations in Ethiopia and Tanzania.

Predictors of psychological resilience amongst medical students following major earthquakes.

PubMed

Carter, Frances; Bell, Caroline; Ali, Anthony; McKenzie, Janice; Boden, Joseph M; Wilkinson, Timothy; Bell, Caroline

2016-05-06

To identify predictors of self-reported psychological resilience amongst medical students following major earthquakes in Canterbury in 2010 and 2011. Two hundred and fifty-three medical students from the Christchurch campus, University of Otago, were invited to participate in an electronic survey seven months following the most severe earthquake. Students completed the Connor-Davidson Resilience Scale, the Depression, Anxiety and Stress Scale, the Post-traumatic Disorder Checklist, the Work and Adjustment Scale, and the Eysenck Personality Questionnaire. Likert scales and other questions were also used to assess a range of variables including demographic and historical variables (eg, self-rated resilience prior to the earthquakes), plus the impacts of the earthquakes. The response rate was 78%. Univariate analyses identified multiple variables that were significantly associated with higher resilience. Multiple linear regression analyses produced a fitted model that was able to explain 35% of the variance in resilience scores. The best predictors of higher resilience were: retrospectively-rated personality prior to the earthquakes (higher extroversion and lower neuroticism); higher self-rated resilience prior to the earthquakes; not being exposed to the most severe earthquake; and less psychological distress following the earthquakes. Psychological resilience amongst medical students following major earthquakes was able to be predicted to a moderate extent.

A Quantile Regression Approach to Understanding the Relations Between Morphological Awareness, Vocabulary, and Reading Comprehension in Adult Basic Education Students

PubMed Central

Tighe, Elizabeth L.; Schatschneider, Christopher

2015-01-01

The purpose of this study was to investigate the joint and unique contributions of morphological awareness and vocabulary knowledge at five reading comprehension levels in Adult Basic Education (ABE) students. We introduce the statistical technique of multiple quantile regression, which enabled us to assess the predictive utility of morphological awareness and vocabulary knowledge at multiple points (quantiles) along the continuous distribution of reading comprehension. To demonstrate the efficacy of our multiple quantile regression analysis, we compared and contrasted our results with a traditional multiple regression analytic approach. Our results indicated that morphological awareness and vocabulary knowledge accounted for a large portion of the variance (82-95%) in reading comprehension skills across all quantiles. Morphological awareness exhibited the greatest unique predictive ability at lower levels of reading comprehension whereas vocabulary knowledge exhibited the greatest unique predictive ability at higher levels of reading comprehension. These results indicate the utility of using multiple quantile regression to assess trajectories of component skills across multiple levels of reading comprehension. The implications of our findings for ABE programs are discussed. PMID:25351773

ℓ(p)-Norm multikernel learning approach for stock market price forecasting.

PubMed

Shao, Xigao; Wu, Kun; Liao, Bifeng

2012-01-01

Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ(1)-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ(p)-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ(1)-norm multiple support vector regression model.

Expression profiling reveals distinct sets of genes altered during induction and regression of cardiac hypertrophy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Friddle, Carl J; Koga, Teiichiro; Rubin, Edward M.

2000-03-15

While cardiac hypertrophy has been the subject of intensive investigation, regression of hypertrophy has been significantly less studied, precluding large-scale analysis of the relationship between these processes. In the present study, using pharmacological models of hypertrophy in mice, expression profiling was performed with fragments of more than 3,000 genes to characterize and contrast expression changes during induction and regression of hypertrophy. Administration of angiotensin II and isoproterenol by osmotic minipump produced increases in heart weight (15% and 40% respectively) that returned to pre-induction size following drug withdrawal. From multiple expression analyses of left ventricular RNA isolated at daily time-points duringmore » cardiac hypertrophy and regression, we identified sets of genes whose expression was altered at specific stages of this process. While confirming the participation of 25 genes or pathways previously known to be altered by hypertrophy, a larger set of 30 genes was identified whose expression had not previously been associated with cardiac hypertrophy or regression. Of the 55 genes that showed reproducible changes during the time course of induction and regression, 32 genes were altered only during induction and 8 were altered only during regression. This study identified both known and novel genes whose expression is affected at different stages of cardiac hypertrophy and regression and demonstrates that cardiac remodeling during regression utilizes a set of genes that are distinct from those used during induction of hypertrophy.« less

Neighborhood street scale elements, sedentary time and cardiometabolic risk factors in inactive ethnic minority women.

PubMed

Lee, Rebecca E; Mama, Scherezade K; Adamus-Leach, Heather J

2012-01-01

Cardiometabolic risk factors such as obesity, excess percent body fat, high blood pressure, elevated resting heart rate and sedentary behavior have increased in recent decades due to changes in the environment and lifestyle. Neighborhood micro-environmental, street scale elements may contribute to health above and beyond individual characteristics of residents. To investigate the relationship between neighborhood street scale elements and cardiometabolic risk factors among inactive ethnic minority women. Women (N = 410) completed measures of BMI, percent body fat, blood pressure, resting heart rate, sedentary behavior and demographics. Trained field assessors completed the Pedestrian Environment Data Scan in participants' neighborhoods. Data were collected from 2006-2008. Multiple regression models were conducted in 2011 to estimate the effect of environmental factors on cardiometabolic risk factors. Adjusted regression models found an inverse association between sidewalk buffers and blood pressure, between traffic control devices and resting heart rate, and a positive association between presence of pedestrian crossing aids and BMI (ps<.05). Neighborhood attractiveness and safety for walking and cycling were related to more time spent in a motor vehicle (ps<.05). Findings suggest complex relationships among micro-environmental, street scale elements that may confer important cardiometabolic benefits and risks for residents. Living in the most attractive and safe neighborhoods for physical activity may be associated with longer times spent sitting in the car.

Development and validation of a short-form Pain Medication Attitudes Questionnaire (PMAQ-14).

PubMed

Elander, James; Said, Omimah; Maratos, Frances A; Dys, Ada; Collins, Hannah; Schofield, Malcolm B

2017-03-01

Attitudes to pain medication are important aspects of adjustment to chronic pain. They are measured by the 47-item Pain Medication Attitudes Questionnaire (PMAQ). To measure those attitudes more quickly and easily, we developed and evaluated a 14-item PMAQ using data from 3 separate surveys of people with pain in the general population. In survey 1, participants (n = 295) completed the 47-item PMAQ and measures of pain, analgesic use, analgesic dependence, and attitudes to self-medication. For each of the 7 PMAQ scales, the 2 items that best preserved the content of the full parent scales were identified using correlation and regression. The 2-item and full parent scales had very similar relationships with other measures, indicating that validity had been maintained. The resulting 14-item PMAQ was then completed by participants in survey 2 (n = 241) and survey 3 (n = 147), along with the same other measures as in survey 1. Confirmatory factor analysis showed that the 14-item PMAQ retained the 7-factor structure of the 47-item version, and correlations with other measures showed that it retained the validity of the 47-item version. The PMAQ scale Need was the most significant independent predictor of analgesic dependence in each of 4 separate multiple regression analyses. This short form of the PMAQ allows attitudes to pain medications to be measured in a valid and more efficient way.

The impact of professional identity on role stress in nursing students: A cross-sectional study.

PubMed

Sun, Li; Gao, Ying; Yang, Juan; Zang, Xiao-Ying; Wang, Yao-Gang

2016-11-01

As newcomers to the clinical workplace, nursing students will encounter a high degree of role stress, which is an important predictor of burnout and engagement. Professional identity is theorised to be a key factor in providing high-quality care to improve patient outcomes and is thought to mediate the negative effects of a high-stress workplace and improve clinical performance and job retention. To investigate the level of nursing students' professional identity and role stress at the end of the first sub-internship, and to explore the impact of the nursing students' professional identity and other characteristics on role stress. A cross-sectional study. Three nursing schools in China. Nursing students after a 6-month sub-internship in a general hospital (n=474). The Role Stress Scale (score range: 12-60) and the Professional Identity Questionnaire for Nursing students (score range: 17-85) were used to investigate the levels of nursing students' role stress and professional identity. Higher scores indicated higher levels of role stress and professional identity. Basic demographic information about the nursing students was collected. The Pearson correlation, point-biserial correlation and multiple linear regression analysis were used to analyse the data. The mean total scores of the Role Stress Scale and Professional Identity Questionnaire for Nursing Students were 34.04 (SD=6.57) and 57.63 (SD=9.63), respectively. In the bivariate analyses, the following independent variables were found to be significantly associated with the total score of the Role Stress Scale: the total score of the Professional Identity Questionnaire for Nursing Students (r=-0.295, p<0.01), age (r=0.145, p<0.01), whether student was an only child or not (r=-0.114, p<0.05), education level (r=0.295, p<0.01) and whether student had experience in community organisations or not (r=0.151, p<0.01). In the multiple linear regression analysis, the total score of the Professional Identity Questionnaire for Nursing Students (standardised coefficient Beta: -0.260, p<0.001), education level (standardised coefficient Beta: 0.212, p<0.001) and whether or not student had experience in community organisations (standardised coefficient Beta: 0.107, p<0.016) were the factors significantly associated with the total score of the Role Stress Scale. The multiple linear regression model explained 18.2% (adjusted R 2 scores 16.5%) of the Role Stress Scale scores variance. The nursing students' level of role stress at the end of the first sub-internship was high. The students with higher professional identity values had lower role stress levels. Compared with other personal characteristics, professional identity and education level had the strongest impact on the nursing students' level of role stress. This is a new perspective that shows that developing and improving professional identity may prove helpful for nursing students in managing role stress. Copyright © 2016 Elsevier Ltd. All rights reserved.

Development and Validation of the ADAS Scale and Prediction of Attitudes Toward Affective-Sexual Diversity Among Spanish Secondary Students.

PubMed

Garrido-Hernansaiz, Helena; Martín-Fernández, Manuel; Castaño-Torrijos, Aida; Cuevas, Isabel

2018-01-01

Violence against non-heterosexual adolescents in educational contexts remains a worrying reality, but no adequate attitudes toward affective-sexual diversity (AtASD) measure exists for Spanish adolescent students. We developed a 27-item scale including cognitive, affective, and behavioral aspects, which was completed by 696 secondary school students from the Madrid area. Factor analyses suggested a unidimensional model, Cronbach's alpha indicated excellent scale scores reliability, and item calibration under the item response theory framework showed that the scale is especially informative for homophobic attitudes. A hierarchical multiple regression analysis showed that variables traditionally related to AtASD (gender, age, religion, nationality, perceived parental/peer attitudes, direct contact with LGB people) also were so in our sample. Moreover, interest in sexuality topics and perceived center's efforts to provide AtASD education were related to better AtASD. Our scale was reliable and valid, and it may also prove useful in efforts to detect those students with homophobic attitudes and to guide interventions.

Multidecadal Variability in Surface Albedo Feedback Across CMIP5 Models

NASA Astrophysics Data System (ADS)

Schneider, Adam; Flanner, Mark; Perket, Justin

2018-02-01

Previous studies quantify surface albedo feedback (SAF) in climate change, but few assess its variability on decadal time scales. Using the Coupled Model Intercomparison Project Version 5 (CMIP5) multimodel ensemble data set, we calculate time evolving SAF in multiple decades from surface albedo and temperature linear regressions. Results are meaningful when temperature change exceeds 0.5 K. Decadal-scale SAF is strongly correlated with century-scale SAF during the 21st century. Throughout the 21st century, multimodel ensemble mean SAF increases from 0.37 to 0.42 W m-2 K-1. These results suggest that models' mean decadal-scale SAFs are good estimates of their century-scale SAFs if there is at least 0.5 K temperature change. Persistent SAF into the late 21st century indicates ongoing capacity for Arctic albedo decline despite there being less sea ice. If the CMIP5 multimodel ensemble results are representative of the Earth, we cannot expect decreasing Arctic sea ice extent to suppress SAF in the 21st century.

Advanced statistics: linear regression, part II: multiple linear regression.

PubMed

Marill, Keith A

2004-01-01

The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

Compulsive use of social networking sites in Belgium: prevalence, profile, and the role of attitude toward work and school.

PubMed

De Cock, Rozane; Vangeel, Jolien; Klein, Annabelle; Minotte, Pascal; Rosas, Omar; Meerkerk, Gert-Jan

2014-03-01

A representative sample (n=1,000) of the Belgian population aged 18 years and older filled out an online questionnaire on their Internet use in general and their use of social networking sites (SNS) in particular. We measured total time spent on the Internet, time spent on SNS, number of SNS profiles, gender, age, schooling level, income, job occupation, and leisure activities, and we integrated several psychological scales such as the Quick Big Five and the Mastery Scale. Hierarchical multiple regression modeling shows that gender and age explain an important part of the compulsive SNS score (5%) as well as psychological scales (20%), but attitude toward school (additional 3%) and income (2.5%) also add to explained variance in predictive models of compulsive SNS use.

Modeling Polytomous Item Responses Using Simultaneously Estimated Multinomial Logistic Regression Models

ERIC Educational Resources Information Center

Anderson, Carolyn J.; Verkuilen, Jay; Peyton, Buddy L.

2010-01-01

Survey items with multiple response categories and multiple-choice test questions are ubiquitous in psychological and educational research. We illustrate the use of log-multiplicative association (LMA) models that are extensions of the well-known multinomial logistic regression model for multiple dependent outcome variables to reanalyze a set of…

MRMPROBS: a data assessment and metabolite identification tool for large-scale multiple reaction monitoring based widely targeted metabolomics.

PubMed

Tsugawa, Hiroshi; Arita, Masanori; Kanazawa, Mitsuhiro; Ogiwara, Atsushi; Bamba, Takeshi; Fukusaki, Eiichiro

2013-05-21

We developed a new software program, MRMPROBS, for widely targeted metabolomics by using the large-scale multiple reaction monitoring (MRM) mode. The strategy became increasingly popular for the simultaneous analysis of up to several hundred metabolites at high sensitivity, selectivity, and quantitative capability. However, the traditional method of assessing measured metabolomics data without probabilistic criteria is not only time-consuming but is often subjective and makeshift work. Our program overcomes these problems by detecting and identifying metabolites automatically, by separating isomeric metabolites, and by removing background noise using a probabilistic score defined as the odds ratio from an optimized multivariate logistic regression model. Our software program also provides a user-friendly graphical interface to curate and organize data matrices and to apply principal component analyses and statistical tests. For a demonstration, we conducted a widely targeted metabolome analysis (152 metabolites) of propagating Saccharomyces cerevisiae measured at 15 time points by gas and liquid chromatography coupled to triple quadrupole mass spectrometry. MRMPROBS is a useful and practical tool for the assessment of large-scale MRM data available to any instrument or any experimental condition.

Meteorological Contribution to Variability in Particulate Matter Concentrations

NASA Astrophysics Data System (ADS)

Woods, H. L.; Spak, S. N.; Holloway, T.

2006-12-01

Local concentrations of fine particulate matter (PM) are driven by a number of processes, including emissions of aerosols and gaseous precursors, atmospheric chemistry, and meteorology at local, regional, and global scales. We apply statistical downscaling methods, typically used for regional climate analysis, to estimate the contribution of regional scale meteorology to PM mass concentration variability at a range of sites in the Upper Midwestern U.S. Multiple years of daily PM10 and PM2.5 data, reported by the U.S. Environmental Protection Agency (EPA), are correlated with large-scale meteorology over the region from the National Centers for Environmental Prediction (NCEP) reanalysis data. We use two statistical downscaling methods (multiple linear regression, MLR, and analog) to identify which processes have the greatest impact on aerosol concentration variability. Empirical Orthogonal Functions of the NCEP meteorological data are correlated with PM timeseries at measurement sites. We examine which meteorological variables exert the greatest influence on PM variability, and which sites exhibit the greatest response to regional meteorology. To evaluate model performance, measurement data are withheld for limited periods, and compared with model results. Preliminary results suggest that regional meteorological processes account over 50% of aerosol concentration variability at study sites.

Possible antecedents and consequences of self-esteem in persons with multiple sclerosis: preliminary evidence from a cross-sectional analysis.

PubMed

Dlugonski, Deirdre; Motl, Robert W

2012-02-01

Persons with multiple sclerosis (MS) have consistently reported lower levels of self-esteem compared with the general population. Despite this, very little is known about the antecedents and consequences of self-esteem in persons with MS. To examine (1) physical activity and social support as potentially modifiable correlates (i.e., antecedents) of self-esteem and (2) physical and psychological health-related quality of life as possible consequences of self-esteem in persons with MS. Participants (N = 46) wore an Actigraph accelerometer for 7 days and then completed a battery of questionnaires, including the Rosenberg Self-Esteem Scale (RSES), Multiple Sclerosis Impact Scale (MSIS-29), and Social Provisions Scale (SPS). The data were analyzed using PASW Statistics 18. Bivariate correlation analysis indicated that average daily step counts (r = .298, p = .026) and social support (r = .366, p = .007) were significantly correlated with self-esteem. Multiple linear regression analysis indicated that only social support was a significant predictor of self-esteem scores (β = .411, p = .004); pedometer steps approached significance as a predictor of self-esteem (β = .178, p = .112). Bivariate correlation analysis further indicated significant negative associations between self-esteem and physical (r = -.391, p = .004) and psychological (r = -.540, p = .0001) domains of health-related quality of life (HRQOL), indicating that higher self-esteem was associated with more positive HRQOL. Social support is a potentially modifiable variable that may be important to target when designing interventions to improve self-esteem and this might have implications for improving physical and psychological HRQOL in persons with MS.

Simultaneous estimation of local-scale and flow path-scale dual-domain mass transfer parameters using geoelectrical monitoring

USGS Publications Warehouse

Briggs, Martin A.; Day-Lewis, Frederick D.; Ong, John B.; Curtis, Gary P.; Lane, John W.

2013-01-01

Anomalous solute transport, modeled as rate-limited mass transfer, has an observable geoelectrical signature that can be exploited to infer the controlling parameters. Previous experiments indicate the combination of time-lapse geoelectrical and fluid conductivity measurements collected during ionic tracer experiments provides valuable insight into the exchange of solute between mobile and immobile porosity. Here, we use geoelectrical measurements to monitor tracer experiments at a former uranium mill tailings site in Naturita, Colorado. We use nonlinear regression to calibrate dual-domain mass transfer solute-transport models to field data. This method differs from previous approaches by calibrating the model simultaneously to observed fluid conductivity and geoelectrical tracer signals using two parameter scales: effective parameters for the flow path upgradient of the monitoring point and the parameters local to the monitoring point. We use regression statistics to rigorously evaluate the information content and sensitivity of fluid conductivity and geophysical data, demonstrating multiple scales of mass transfer parameters can simultaneously be estimated. Our results show, for the first time, field-scale spatial variability of mass transfer parameters (i.e., exchange-rate coefficient, porosity) between local and upgradient effective parameters; hence our approach provides insight into spatial variability and scaling behavior. Additional synthetic modeling is used to evaluate the scope of applicability of our approach, indicating greater range than earlier work using temporal moments and a Lagrangian-based Damköhler number. The introduced Eulerian-based Damköhler is useful for estimating tracer injection duration needed to evaluate mass transfer exchange rates that range over several orders of magnitude.

Career-Success Scale – A new instrument to assess young physicians' academic career steps

PubMed Central

Buddeberg-Fischer, Barbara; Stamm, Martina; Buddeberg, Claus; Klaghofer, Richard

2008-01-01

Background Within the framework of a prospective cohort study of Swiss medical school graduates, a Career-Success Scale (CSS) was constructed in a sample of young physicians choosing different career paths in medicine. Furthermore the influence of personality factors, the participants' personal situation, and career related factors on their career success was investigated. Methods 406 residents were assessed in terms of career aspired to, and their career progress. The Career-Success Scale, consisting of 7 items, was developed and validated, addressing objective criteria of academic career advancement. The influence of gender and career aspiration was investigated by a two-factorial analysis of variance, the relationships between personality factors, personal situation, career related factors and the Career-Success Scale by a multivariate linear regression analysis. Results The unidimensional Career-Success Scale has an internal consistency of 0.76. It is significantly correlated at the bivariate level with gender, instrumentality, and all career related factors, particularly with academic career and received mentoring. In multiple regression, only gender, academic career, surgery as chosen specialty, and received mentoring are significant predictors. The highest values were observed in participants aspiring to an academic career, followed by those pursuing a hospital career and those wanting to run a private practice. Independent of the career aspired to, female residents have lower scores than their male colleagues. Conclusion The Career-Success Scale proved to be a short, reliable and valid instrument to measure career achievements. As mentoring is an independent predictor of career success, mentoring programs could be an important instrument to specifically enhance careers of female physicians in academia. PMID:18518972

Career-success scale - a new instrument to assess young physicians' academic career steps.

PubMed

Buddeberg-Fischer, Barbara; Stamm, Martina; Buddeberg, Claus; Klaghofer, Richard

2008-06-02

Within the framework of a prospective cohort study of Swiss medical school graduates, a Career-Success Scale (CSS) was constructed in a sample of young physicians choosing different career paths in medicine. Furthermore the influence of personality factors, the participants' personal situation, and career related factors on their career success was investigated. 406 residents were assessed in terms of career aspired to, and their career progress. The Career-Success Scale, consisting of 7 items, was developed and validated, addressing objective criteria of academic career advancement. The influence of gender and career aspiration was investigated by a two-factorial analysis of variance, the relationships between personality factors, personal situation, career related factors and the Career-Success Scale by a multivariate linear regression analysis. The unidimensional Career-Success Scale has an internal consistency of 0.76. It is significantly correlated at the bivariate level with gender, instrumentality, and all career related factors, particularly with academic career and received mentoring. In multiple regression, only gender, academic career, surgery as chosen specialty, and received mentoring are significant predictors. The highest values were observed in participants aspiring to an academic career, followed by those pursuing a hospital career and those wanting to run a private practice. Independent of the career aspired to, female residents have lower scores than their male colleagues. The Career-Success Scale proved to be a short, reliable and valid instrument to measure career achievements. As mentoring is an independent predictor of career success, mentoring programs could be an important instrument to specifically enhance careers of female physicians in academia.

EPA Office of Water (OW): 2002 SPARROW Total NP (Catchments)

EPA Pesticide Factsheets

SPARROW (SPAtially Referenced Regressions On Watershed attributes) is a watershed modeling tool with output that allows the user to interpret water quality monitoring data at the regional and sub-regional scale. The model relates in-stream water-quality measurements to spatially referenced characteristics of watersheds, including pollutant sources and environmental factors that affect rates of pollutant delivery to streams from the land and aquatic, in-stream processing . The core of the model consists of a nonlinear regression equation describing the non-conservative transport of contaminants from point and non-point (or ??diffuse??) sources on land to rivers and through the stream and river network. SPARROW estimates contaminant concentrations, loads (or ??mass,?? which is the product of concentration and streamflow), and yields in streams (mass of nitrogen and of phosphorus entering a stream per acre of land). It empirically estimates the origin and fate of contaminants in streams and receiving bodies, and quantifies uncertainties in model predictions. The model predictions are illustrated through detailed maps that provide information about contaminant loadings and source contributions at multiple scales for specific stream reaches, basins, or other geographic areas.

Depression and pain: independent and additive relationships to anger expression.

PubMed

Taylor, Marcus K; Larson, Gerald E; Norman, Sonya B

2013-10-01

Anger and anger expression (ANGX) are concerns in the U.S. military population and have been linked to stress dysregulation, heart disease, and poor coping behaviors. We examined associations between depression, pain, and anger expression among military veterans. Subjects (N = 474) completed a depression scale, a measure of pain across the last 4 weeks, and an ANGX scale. A multiple regression model assessed the independent and additive relationships of depression and pain to ANGX. Almost 40% of subjects met the case definition for either major or minor depression. Subjects reported low-to-moderate levels of pain (mean = 6.3 of possible 20) and somewhat frequent episodes of ANGX. As expected, depression and pain were positively associated (r = 0.42, p < 0.001) and crossover effects of antidepressant and pain medication were shown. Specifically, frequency of antidepressant medication use was inversely associated with pain symptoms (r = -0.20, p < 0.001) and frequency of pain medication use was inversely linked to depressive symptoms (r = -0.21, p < 0.001). In a multiple regression model, depression (β = 0.58, p < 0.001) and pain (β = 0.21, p < 0.05) showed independent and additive relationships to ANGX (F = 41.5, p < 0.001, R(2)adj = 0.31). This study offers empirical support for depression-pain comorbidity and elucidates independent and additive contributions of depression and pain to ANGX. Reprint & Copyright © 2013 Association of Military Surgeons of the U.S.

Stoichiometry of hydrological C, N, and P losses across climate and geology: An environmental matrix approach across New Zealand primary forests

NASA Astrophysics Data System (ADS)

McGroddy, M. E.; Baisden, W. T.; Hedin, L. O.

2008-03-01

Hydrologic losses can play a key role in regulating ecosystem nutrient balances, particularly in regions where baseline nutrient cycles are not augmented by industrial deposition. We used first-order streams to integrate hydrologic losses at the watershed scale across unpolluted old-growth forests in New Zealand. We employed a matrix approach to resolve how stream water concentrations of dissolved organic carbon (DOC), organic and inorganic nitrogen (DON and DIN), and organic and inorganic phosphorus (DOP and DIP) varied as a function of landscape differences in climate and geology. We found stream water total dissolved nitrogen (TDN) to be dominated by organic forms (medians for DON, 81.3%, nitrate-N, 12.6%, and ammonium-N, 3.9%). The median stream water DOC:TDN:TDP molar ratio of 1050:21:1 favored C slightly over N and P when compared to typical temperate forest foliage ratios. Using the full set of variables in a multiple regression approach explained approximately half of the variability in DON, DOC, and TDP concentrations. Building on this approach we combined a simplified set of variables with a simple water balance model in a regression designed to predict DON export at larger spatial scales. Incorporating the effects of climate and geologic variables on nutrient exports will greatly aid the development of integrated Earth-climate biogeochemical models which are able to take into account multiple element dynamics and complex natural landscapes.

Application of WHOQOL-BREF in Measuring Quality of Life in Health-Care Staff.

PubMed

Gholami, Ali; Jahromi, Leila Moosavi; Zarei, Esmail; Dehghan, Azizallah

2013-07-01

The objective of this study was to evaluate the quality of life of Neyshabur health-care staff and some factors associated with it with use of WHOQOL-BREF scale. This cross-sectional study was conducted on 522 staff of Neyshabur health-care centers from May to July 2011. Cronbach's alpha coefficient was applied to examine the internal consistency of WHOQOL-BREF scale; Pearson's correlation coefficient was used to determine the level of agreement between different domains of WHOQOL-BREF. Paired t-test was used to compare difference between score means of different domains. T-independent test was performed for group analysis and Multiple Linear Regression was used to control confounding effects. In this study, a good internal consistency (α = 0.925) for WHOQOL-BREF and its four domains was observed. The highest and the lowest mean scores of WHOQOL-BREF domains was found for physical health domain (Mean = 15.26) and environmental health domain (Mean = 13.09) respectively. Backward multiple linear regression revealed that existence chronic disease in staff was significantly associated with four domains of WHOQOL-BREF, education years was associated with two domains (Psychological and Environmental) and sex was associated with psychological domain (P < 0.05). The findings from this study confirm that the WHOQOL-BREF questionnaire is a reliable instrument to measure quality of life in health-care staff. From the data, it appears that Neyshabur health-care staff has WHOQOL-BREF scores that might be considered to indicate a relatively moderate quality of life.

Impaired executive function can predict recurrent falls in Parkinson's disease.

PubMed

Mak, Margaret K; Wong, Adrian; Pang, Marco Y

2014-12-01

To examine whether impairment in executive function independently predicts recurrent falls in people with Parkinson's disease (PD). Prospective cohort study. University motor control research laboratory. A convenience sample of community-dwelling people with PD (N=144) was recruited from a patient self-help group and movement disorders clinics. Not applicable. Executive function was assessed with the Mattis Dementia Rating Scale Initiation/Perseveration (MDRS-IP) subtest, and fear of falling (FoF) with the Activities-specific Balance Confidence (ABC) Scale. All participants were followed up for 12 months to record the number of monthly fall events. Forty-two people with PD had at least 2 falls during the follow-up period and were classified as recurrent fallers. After accounting for demographic variables and fall history (P=.001), multiple logistic regression analysis showed that the ABC scores (P=.014) and MDRS-IP scores (P=.006) were significantly associated with future recurrent falls among people with PD. The overall accuracy of the prediction was 85.9%. With the use of the significant predictors identified in multiple logistic regression analysis, a prediction model determined by the logistic function was generated: Z = 1.544 + .378 (fall history) - .045 (ABC) - .145 (MDRS-IP). Impaired executive function is a significant predictor of future recurrent falls in people with PD. Participants with executive dysfunction and greater FoF at baseline had a significantly greater risk of sustaining a recurrent fall within the subsequent 12 months. Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Isolating and Examining Sources of Suppression and Multicollinearity in Multiple Linear Regression

ERIC Educational Resources Information Center

Beckstead, Jason W.

2012-01-01

The presence of suppression (and multicollinearity) in multiple regression analysis complicates interpretation of predictor-criterion relationships. The mathematical conditions that produce suppression in regression analysis have received considerable attention in the methodological literature but until now nothing in the way of an analytic…

General Nature of Multicollinearity in Multiple Regression Analysis.

ERIC Educational Resources Information Center

Liu, Richard

1981-01-01

Discusses multiple regression, a very popular statistical technique in the field of education. One of the basic assumptions in regression analysis requires that independent variables in the equation should not be highly correlated. The problem of multicollinearity and some of the solutions to it are discussed. (Author)

Illness perception, treatment beliefs, self-esteem, and self-efficacy as correlates of self-management in multiple sclerosis.

PubMed

Wilski, M; Tasiemski, T

2016-05-01

Self-management of a disease is considered one of the most important factors affecting the treatment outcome. The research on the correlates of self-management in multiple sclerosis (MS) is limited. The aim of this study was to determine if personal factors, such as illness perception, treatment beliefs, self-esteem and self-efficacy, are correlates of self-management in MS. This cross-sectional study included 210 patients with MS who completed Multiple Sclerosis Self-Management Scale - Revised, Brief Illness Perception Questionnaire, Treatment Beliefs Scale, Rosenberg Self-Esteem Scale, and Generalized Self-Efficacy Scale. The patients were recruited from a MS rehabilitation clinic. Demographic data and illness-related problems of the study participants were collected with a self-report survey. Correlation and regression analyses were performed to determine associations between variables. Four factors: age at the time of the study (β = 0.14, P = 0.032), timeline (β = 0.16, P = 0.018), treatment control (β = 0.17, P = 0.022), and general self-efficacy (β = 0.19, P = 0.014) turned out to be the significant correlates of self-management in MS. The model including these variables explained 25% of variance in self-management in MS. Personal factors, such as general self-efficacy, perception of treatment control and realistic MS timeline perspective, are more salient correlates of self-management in MS than the objective clinical variables, such as the severity, type, and duration of MS. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

ℓ p-Norm Multikernel Learning Approach for Stock Market Price Forecasting

PubMed Central

Shao, Xigao; Wu, Kun; Liao, Bifeng

2012-01-01

Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ 1-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ p-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ 1-norm multiple support vector regression model. PMID:23365561

Sample size determination for logistic regression on a logit-normal distribution.

PubMed

Kim, Seongho; Heath, Elisabeth; Heilbrun, Lance

2017-06-01

Although the sample size for simple logistic regression can be readily determined using currently available methods, the sample size calculation for multiple logistic regression requires some additional information, such as the coefficient of determination ([Formula: see text]) of a covariate of interest with other covariates, which is often unavailable in practice. The response variable of logistic regression follows a logit-normal distribution which can be generated from a logistic transformation of a normal distribution. Using this property of logistic regression, we propose new methods of determining the sample size for simple and multiple logistic regressions using a normal transformation of outcome measures. Simulation studies and a motivating example show several advantages of the proposed methods over the existing methods: (i) no need for [Formula: see text] for multiple logistic regression, (ii) available interim or group-sequential designs, and (iii) much smaller required sample size.

Correlates of motivation to change in pathological gamblers completing cognitive-behavioral group therapy.

PubMed

Gómez-Peña, Mónica; Penelo, Eva; Granero, Roser; Fernández-Aranda, Fernando; Alvarez-Moya, Eva; Santamaría, Juan José; Moragas, Laura; Neus Aymamí, Maria; Gunnard, Katarina; Menchón, José M; Jimenez-Murcia, Susana

2012-07-01

The present study analyzes the association between the motivation to change and the cognitive-behavioral group intervention, in terms of dropouts and relapses, in a sample of male pathological gamblers. The specific objectives were as follows: (a) to estimate the predictive value of baseline University of Rhode Island Change Assessment scale (URICA) scores (i.e., at the start of the study) as regards the risk of relapse and dropout during treatment and (b) to assess the incremental predictive ability of URICA scores, as regards the mean change produced in the clinical status of patients between the start and finish of treatment. The relationship between the URICA and the response to treatment was analyzed by means of a pre-post design applied to a sample of 191 patients who were consecutively receiving cognitive-behavioral group therapy. The statistical analysis included logistic regression models and hierarchical multiple linear regression models. The discriminative ability of the models including the four URICA scores regarding the likelihood of relapse and dropout was acceptable (area under the receiver operating haracteristic curve: .73 and .71, respectively). No significant predictive ability was found as regards the differences between baseline and posttreatment scores (changes in R(2) below 5% in the multiple regression models). The availability of useful measures of motivation to change would enable treatment outcomes to be optimized through the application of specific therapeutic interventions. © 2012 Wiley Periodicals, Inc.

Estimating Time to Event From Longitudinal Categorical Data: An Analysis of Multiple Sclerosis Progression.

PubMed

Mandel, Micha; Gauthier, Susan A; Guttmann, Charles R G; Weiner, Howard L; Betensky, Rebecca A

2007-12-01

The expanded disability status scale (EDSS) is an ordinal score that measures progression in multiple sclerosis (MS). Progression is defined as reaching EDSS of a certain level (absolute progression) or increasing of one point of EDSS (relative progression). Survival methods for time to progression are not adequate for such data since they do not exploit the EDSS level at the end of follow-up. Instead, we suggest a Markov transitional model applicable for repeated categorical or ordinal data. This approach enables derivation of covariate-specific survival curves, obtained after estimation of the regression coefficients and manipulations of the resulting transition matrix. Large sample theory and resampling methods are employed to derive pointwise confidence intervals, which perform well in simulation. Methods for generating survival curves for time to EDSS of a certain level, time to increase of EDSS of at least one point, and time to two consecutive visits with EDSS greater than three are described explicitly. The regression models described are easily implemented using standard software packages. Survival curves are obtained from the regression results using packages that support simple matrix calculation. We present and demonstrate our method on data collected at the Partners MS center in Boston, MA. We apply our approach to progression defined by time to two consecutive visits with EDSS greater than three, and calculate crude (without covariates) and covariate-specific curves.

The association between financial literacy and Problematic Internet Shopping in a multinational sample.

PubMed

Lam, Lawrence T; Lam, Mary K

2017-12-01

To examine the association between financial literacy and Problematic Internet Shopping in adults. This cross-sectional online survey recruited participants, aged between 18 and 60 years, through an online research facility. The sample consisted of multinational participants from mainly three continents including Europe, North America, and Asia. Problematic Internet Shopping was assessed using the Bergen Shopping Addiction Scale (BSAS). Financial Literacy was measured by the Financial Literacy subscale of the Financial Wellbeing Questionnaire. Multiple linear regression analyses were conducted to elucidate the relationship between the study and outcome variables with adjustment for other potential risk factors. Of the total of 997 respondents with an average age of 30.9 (s.d. = 8.8), 135 (13.8%) could be classified as having a high risk of being Problematic Internet Shoppers. Results from the multiple regression analyses suggested a significant and negative relationship between financial literacy and Problematic Internet Shopping with a regression coefficient of - 0.13, after controlling for the effects of potential risk factors such as age, region of birth, employment, income, shopping frequency, self-regulation and anxiety (t = - 6.42, p < 0.001). The clinical management of PIS should include a financial counselling as a component of the treatment regime. Enhancement of financial literacy in the general population, particularly among young people, will likely have a positive effect on the occurrence of PIS.

Investigation of marital satisfaction and its relationship with job stress and general health of nurses in Qazvin, Iran

PubMed Central

Azimian, Jalil; Piran, Pegah; Jahanihashemi, Hassan; Dehghankar, Leila

2017-01-01

Background Pressures in nursing can affect family life and marital problems, disrupt common social problems, increase work-family conflicts and endanger people’s general health. Aim To determine marital satisfaction and its relationship with job stress and general health of nurses. Methods This descriptive and cross-sectional study was done in 2015 in medical educational centers of Qazvin by using an ENRICH marital satisfaction scale and General Health and Job Stress questionnaires completed by 123 nurses. Analysis was done by SPSS version 19 using descriptive and analytical statistics (Pearson correlation, t-test, ANOVA, Chi-square, regression line, multiple regression analysis). Results The findings showed that 64.4% of nurses had marital satisfaction. There was significant relationship between age (p=0.03), job experience (p=0.01), age of spouse (p=0.01) and marital satisfaction. The results showed that there was a significant relationship between marital satisfaction and general health (p<0.0001). Multiple regression analysis showed that there was a significant relationship between depression (p=0.012) and anxiety (p=0.001) with marital satisfaction. Conclusions Due to high levels of job stress and disorder in general health of nurses and low marital satisfaction by running health promotion programs and paying attention to its dimensions can help work and family health of nurses. PMID:28607660

Daily Suspended Sediment Discharge Prediction Using Multiple Linear Regression and Artificial Neural Network

NASA Astrophysics Data System (ADS)

Uca; Toriman, Ekhwan; Jaafar, Othman; Maru, Rosmini; Arfan, Amal; Saleh Ahmar, Ansari

2018-01-01

Prediction of suspended sediment discharge in a catchments area is very important because it can be used to evaluation the erosion hazard, management of its water resources, water quality, hydrology project management (dams, reservoirs, and irrigation) and to determine the extent of the damage that occurred in the catchments. Multiple Linear Regression analysis and artificial neural network can be used to predict the amount of daily suspended sediment discharge. Regression analysis using the least square method, whereas artificial neural networks using Radial Basis Function (RBF) and feedforward multilayer perceptron with three learning algorithms namely Levenberg-Marquardt (LM), Scaled Conjugate Descent (SCD) and Broyden-Fletcher-Goldfarb-Shanno Quasi-Newton (BFGS). The number neuron of hidden layer is three to sixteen, while in output layer only one neuron because only one output target. The mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (R2 ) and coefficient of efficiency (CE) of the multiple linear regression (MLRg) value Model 2 (6 input variable independent) has the lowest the value of MAE and RMSE (0.0000002 and 13.6039) and highest R2 and CE (0.9971 and 0.9971). When compared between LM, SCG and RBF, the BFGS model structure 3-7-1 is the better and more accurate to prediction suspended sediment discharge in Jenderam catchment. The performance value in testing process, MAE and RMSE (13.5769 and 17.9011) is smallest, meanwhile R2 and CE (0.9999 and 0.9998) is the highest if it compared with the another BFGS Quasi-Newton model (6-3-1, 9-10-1 and 12-12-1). Based on the performance statistics value, MLRg, LM, SCG, BFGS and RBF suitable and accurately for prediction by modeling the non-linear complex behavior of suspended sediment responses to rainfall, water depth and discharge. The comparison between artificial neural network (ANN) and MLRg, the MLRg Model 2 accurately for to prediction suspended sediment discharge (kg/day) in Jenderan catchment area.

Impact of External Price Referencing on Medicine Prices – A Price Comparison Among 14 European Countries

PubMed Central

Leopold, Christine; Mantel-Teeuwisse, Aukje Katja; Seyfang, Leonhard; Vogler, Sabine; de Joncheere, Kees; Laing, Richard Ogilvie; Leufkens, Hubert

2012-01-01

Objectives: This study aims to examine the impact of external price referencing (EPR) on on-patent medicine prices, adjusting for other factors that may affect price levels such as sales volume, exchange rates, gross domestic product (GDP) per capita, total pharmaceutical expenditure (TPE), and size of the pharmaceutical industry. Methods: Price data of 14 on-patent products, in 14 European countries in 2007 and 2008 were obtained from the Pharmaceutical Price Information Service of the Austrian Health Institute. Based on the unit ex-factory prices in EURO, scaled ranks per country and per product were calculated. For the regression analysis the scaled ranks per country and product were weighted; each country had the same sum of weights but within a country the weights were proportional to its sales volume in the year (data obtained from IMS Health). Taking the scaled ranks, several statistical analyses were performed by using the program “R”, including a multiple regression analysis (including variables such as GDP per capita and national industry size). Results: This study showed that on average EPR as a pricing policy leads to lower prices. However, the large variation in price levels among countries using EPR confirmed that the price level is not only driven by EPR. The unadjusted linear regression model confirms that applying EPR in a country is associated with a lower scaled weighted rank (p=0.002). This interaction persisted after inclusion of total pharmaceutical expenditure per capita and GDP per capita in the final model. Conclusions: The study showed that for patented products, prices are in general lower in case the country applied EPR. Nevertheless substantial price differences among countries that apply EPR could be identified. Possible explanations could be found through a correlation between pharmaceutical industry and the scaled price ranks. In conclusion, we found that implementing external reference pricing could lead to lower prices. PMID:23532710

Combined chamber-tower approach: Using eddy covariance measurements to cross-validate carbon fluxes modeled from manual chamber campaigns

NASA Astrophysics Data System (ADS)

Brümmer, C.; Moffat, A. M.; Huth, V.; Augustin, J.; Herbst, M.; Kutsch, W. L.

2016-12-01

Manual carbon dioxide flux measurements with closed chambers at scheduled campaigns are a versatile method to study management effects at small scales in multiple-plot experiments. The eddy covariance technique has the advantage of quasi-continuous measurements but requires large homogeneous areas of a few hectares. To evaluate the uncertainties associated with interpolating from individual campaigns to the whole vegetation period, we installed both techniques at an agricultural site in Northern Germany. The presented comparison covers two cropping seasons, winter oilseed rape in 2012/13 and winter wheat in 2013/14. Modeling half-hourly carbon fluxes from campaigns is commonly performed based on non-linear regressions for the light response and respiration. The daily averages of net CO2 modeled from chamber data deviated from eddy covariance measurements in the range of ± 5 g C m-2 day-1. To understand the observed differences and to disentangle the effects, we performed four additional setups (expert versus default settings of the non-linear regressions based algorithm, purely empirical modeling with artificial neural networks versus non-linear regressions, cross-validating using eddy covariance measurements as campaign fluxes, weekly versus monthly scheduling of campaigns) to model the half-hourly carbon fluxes for the whole vegetation period. The good agreement of the seasonal course of net CO2 at plot and field scale for our agricultural site demonstrates that both techniques are robust and yield consistent results at seasonal time scale even for a managed ecosystem with high temporal dynamics in the fluxes. This allows combining the respective advantages of factorial experiments at plot scale with dense time series data at field scale. Furthermore, the information from the quasi-continuous eddy covariance measurements can be used to derive vegetation proxies to support the interpolation of carbon fluxes in-between the manual chamber campaigns.

Prevalence and some psychosocial characteristics of social anxiety disorder in an urban population of Turkish children and adolescents.

PubMed

Demir, T; Karacetin, G; Eralp Demir, D; Uysal, O

2013-01-01

To define the prevalence and some of the psychosocial characteristics of social anxiety disorder (SAD) in an urban population of Turkish children and adolescents. This was a two-stage cross-sectional urban-based study conducted in Fatih, Istanbul, Turkey. The initial sample included 1,482 students between the 4th and 8th grades. The first stage involved screening using the Social Anxiety Scale for Children-Revised (SASC-R) and the Capa Social Phobia Scale for Children and Adolescents (CSPSCA). According to the test results, 324 children were interviewed using the Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version (K-SADS-PL) in the second stage. The SAD prevalence rate was 3.9%. According to the multiple regression analysis, low paternal education and trait anxiety were associated with SASC-R scores, whereas female gender and trait anxiety were associated with CSPSCA scores. According to logistic regression analysis, the anxiety subscale of the self-concept scale and trait anxiety were associated with SAD. SAD is a relatively common disorder that is associated with lower self-concept in children and adolescents. Low paternal education, trait anxiety, and low self-concept may be the intervention targets for SAD prevention and treatment. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

Development of brief versions of the Wechsler Intelligence Scale for schizophrenia: considerations of the structure and predictability of intelligence.

PubMed

Sumiyoshi, Chika; Uetsuki, Miki; Suga, Motomu; Kasai, Kiyoto; Sumiyoshi, Tomiki

2013-12-30

Short forms (SF) of the Wechsler Intelligence Scale have been developed to enhance its practicality. However, only a few studies have addressed the Wechsler Intelligence Scale Revised (WAIS-R) SFs based on data from patients with schizophrenia. The current study was conducted to develop the WAIS-R SFs for these patients based on the intelligence structure and predictability of the Full IQ (FIQ). Relations to demographic and clinical variables were also examined on selecting plausible subtests. The WAIS-R was administered to 90 Japanese patients with schizophrenia. Exploratory factor analysis (EFA) and multiple regression analysis were conducted to find potential subtests. EFA extracted two dominant factors corresponding to Verbal IQ and Performance IQ measures. Subtests with higher factor loadings on those factors were initially nominated. Regression analysis was carried out to reach the model containing all the nominated subtests. The optimality of the potential subtests included in that model was evaluated from the perspectives of the representativeness of intelligence structure, FIQ predictability, and the relation with demographic and clinical variables. Taken together, the dyad of Vocabulary and Block Design was considered to be the most optimal WAIS-R SF for patients with schizophrenia, reflecting both intelligence structure and FIQ predictability. © 2013 Elsevier Ireland Ltd. All rights reserved.

[Study of blending method for the extracts of herbal plants].

PubMed

Liu, Yongsuo; Cao, Min; Chen, Yuying; Hu, Yuzhu; Wang, Yiming; Luo, Guoan

2006-03-01

The irregularity in herbal plant composition is influenced by multiple factors. As for quality control of traditional Chinese medicine, the most critical challenge is to ensure the dosage content uniformity. This content uniformity can be improved by blending different batches of the extracts of herbal plants. Nonlinear least-squares regression was used to calculate the blending coefficient, which means no great absolute differences allowed for all ingredients. For traditional Chinese medicines, even relatively smaller differences could present to be very important for all the ingredients. The auto-scaling pretreatment was used prior to the calculation of the blending coefficients. The pretreatment buffered the characteristics of individual data for the ingredients in different batches, so an improved auto-scaling pretreatment method was proposed. With the improved auto-scaling pretreatment, the relative. differences decreased after blending different batches of extracts of herbal plants according to the reference samples. And the content uniformity control of the specific ingredients could be achieved by the error control coefficient. In the studies for the extracts of fructus gardeniae, the relative differences of all the ingredients is less than 3% after blending different batches of the extracts. The results showed that nonlinear least-squares regression can be used to calculate the blending coefficient of the herbal plant extracts.

Real-world implications of apathy among older adults: Independent associations with activities of daily living and quality of life.

PubMed

Tierney, Savanna M; Woods, Steven Paul; Weinborn, Michael; Bucks, Romola S

2018-03-13

Apathy is common in older adults and has been linked to adverse health outcomes. The current study examined whether apathy contributes to problems managing activities of daily living (ADLs) and lower quality of life (QoL) in older adults. Participants included 83 community-dwelling older adults. Apathy was assessed using a composite of the self and family-rating scales from the Frontal Systems Behavioral Scale (FrSBe). A knowledgeable informant completed the Activities of Daily Living Questionnaire (ADLQ), and participants completed the World Health Organization Quality of Life (WHOQol) scale. Nominal logistic regressions controlling for age, anxiety and depression symptoms, chronic medical conditions, and global cognition revealed that higher levels of apathy were significantly associated with a wide range of mild ADL problems. In parallel, a multiple linear regression indicated that greater apathy was significantly associated with lower QoL independent of ADL problems, anxious and depressive symptomology, chronic medical conditions, global cognition and age. Findings suggest that apathy confers an increased risk of problems in the independent management of daily activities and poorer well-being among community-dwelling older adults. Neurobehavioral and pharmacological interventions to improve apathy may have beneficial effects on the daily lives of older adults.

Comparative study of outcome measures and analysis methods for traumatic brain injury trials.

PubMed

Alali, Aziz S; Vavrek, Darcy; Barber, Jason; Dikmen, Sureyya; Nathens, Avery B; Temkin, Nancy R

2015-04-15

Batteries of functional and cognitive measures have been proposed as alternatives to the Extended Glasgow Outcome Scale (GOSE) as the primary outcome for traumatic brain injury (TBI) trials. We evaluated several approaches to analyzing GOSE and a battery of four functional and cognitive measures. Using data from a randomized trial, we created a "super" dataset of 16,550 subjects from patients with complete data (n=331) and then simulated multiple treatment effects across multiple outcome measures. Patients were sampled with replacement (bootstrapping) to generate 10,000 samples for each treatment effect (n=400 patients/group). The percentage of samples where the null hypothesis was rejected estimates the power. All analytic techniques had appropriate rates of type I error (≤5%). Accounting for baseline prognosis either by using sliding dichotomy for GOSE or using regression-based methods substantially increased the power over the corresponding analysis without accounting for prognosis. Analyzing GOSE using multivariate proportional odds regression or analyzing the four-outcome battery with regression-based adjustments had the highest power, assuming equal treatment effect across all components. Analyzing GOSE using a fixed dichotomy provided the lowest power for both unadjusted and regression-adjusted analyses. We assumed an equal treatment effect for all measures. This may not be true in an actual clinical trial. Accounting for baseline prognosis is critical to attaining high power in Phase III TBI trials. The choice of primary outcome for future trials should be guided by power, the domain of brain function that an intervention is likely to impact, and the feasibility of collecting outcome data.

Comparative Study of Outcome Measures and Analysis Methods for Traumatic Brain Injury Trials

PubMed Central

Alali, Aziz S.; Vavrek, Darcy; Barber, Jason; Dikmen, Sureyya; Nathens, Avery B.

2015-01-01

Abstract Batteries of functional and cognitive measures have been proposed as alternatives to the Extended Glasgow Outcome Scale (GOSE) as the primary outcome for traumatic brain injury (TBI) trials. We evaluated several approaches to analyzing GOSE and a battery of four functional and cognitive measures. Using data from a randomized trial, we created a “super” dataset of 16,550 subjects from patients with complete data (n=331) and then simulated multiple treatment effects across multiple outcome measures. Patients were sampled with replacement (bootstrapping) to generate 10,000 samples for each treatment effect (n=400 patients/group). The percentage of samples where the null hypothesis was rejected estimates the power. All analytic techniques had appropriate rates of type I error (≤5%). Accounting for baseline prognosis either by using sliding dichotomy for GOSE or using regression-based methods substantially increased the power over the corresponding analysis without accounting for prognosis. Analyzing GOSE using multivariate proportional odds regression or analyzing the four-outcome battery with regression-based adjustments had the highest power, assuming equal treatment effect across all components. Analyzing GOSE using a fixed dichotomy provided the lowest power for both unadjusted and regression-adjusted analyses. We assumed an equal treatment effect for all measures. This may not be true in an actual clinical trial. Accounting for baseline prognosis is critical to attaining high power in Phase III TBI trials. The choice of primary outcome for future trials should be guided by power, the domain of brain function that an intervention is likely to impact, and the feasibility of collecting outcome data. PMID:25317951

A Quantile Regression Approach to Understanding the Relations Among Morphological Awareness, Vocabulary, and Reading Comprehension in Adult Basic Education Students.

PubMed

Tighe, Elizabeth L; Schatschneider, Christopher

2016-07-01

The purpose of this study was to investigate the joint and unique contributions of morphological awareness and vocabulary knowledge at five reading comprehension levels in adult basic education (ABE) students. We introduce the statistical technique of multiple quantile regression, which enabled us to assess the predictive utility of morphological awareness and vocabulary knowledge at multiple points (quantiles) along the continuous distribution of reading comprehension. To demonstrate the efficacy of our multiple quantile regression analysis, we compared and contrasted our results with a traditional multiple regression analytic approach. Our results indicated that morphological awareness and vocabulary knowledge accounted for a large portion of the variance (82%-95%) in reading comprehension skills across all quantiles. Morphological awareness exhibited the greatest unique predictive ability at lower levels of reading comprehension whereas vocabulary knowledge exhibited the greatest unique predictive ability at higher levels of reading comprehension. These results indicate the utility of using multiple quantile regression to assess trajectories of component skills across multiple levels of reading comprehension. The implications of our findings for ABE programs are discussed. © Hammill Institute on Disabilities 2014.

Stepwise versus Hierarchical Regression: Pros and Cons

ERIC Educational Resources Information Center

Lewis, Mitzi

2007-01-01

Multiple regression is commonly used in social and behavioral data analysis. In multiple regression contexts, researchers are very often interested in determining the "best" predictors in the analysis. This focus may stem from a need to identify those predictors that are supportive of theory. Alternatively, the researcher may simply be interested…

The moderator-mediator role of social support in early adolescents.

PubMed

Yarcheski, A; Mahon, N E

1999-10-01

The purpose of this study was to examine social support as both a mediator and a moderator of the relationship between perceived stress and symptom patterns in early adolescents. Data were collected from 148 early adolescent boys and girls, ages 12 to 14, who responded to the Perceived Stress Scale, the Personal Resource Questionnaire 85-Part II, and the Symptom Pattern Scale. Using multiple regression analysis procedures specified for the testing of moderation and mediation, results indicated that social support did not play a moderating role in the relationship between perceived stress and symptom patterns, but social support did play a mediating role in this relationship. The findings are interpreted within the two major theoretical orientations that guided the study.

Changes in personality traits during treatment with sertraline or citalopram.

PubMed

Ekselius, L; Von Knorring, L

1999-05-01

Recent studies indicate that selective serotonin re-uptake inhibitors (SSRIs) reduce the symptoms accompanying personality disorders and modulate a normal personality. To examine the effect of two SSRIs, sertraline and citalopram, on personality traits in major depressed patients. Personality traits were evaluated at baseline and after six months using the Karolinska Scales of Personality (KSP). After treatment, significant changes in the direction of normalisation were seen in all scales. To determine whether the observed changes could be explained by improved depressive symptoms, multiple stepwise regressions with the separate KSP as dependent variables were performed. Improvements in depressive symptoms only accounted for 0-8.4% of the observed variance. In depressed patients treated with SSRIs significant effects are seen on personality traits measured by the KSP.

Personality and emotional intelligence in teacher burnout.

PubMed

Pishghadam, Reza; Sahebjam, Samaneh

2012-03-01

This paper aims to investigate the relationship between teacher's personality types, emotional intelligence and burnout and to predict the burnout levels of 147 teachers in the city of Mashhad (Iran). To this end, we have used three inventories: Maslach Burnout Inventory (MBI), NEO Five Factor Inventory (NEO-FFI), and Emotional Quotient Inventory (EQ-I). We used Homogeneity Analysis and Multiple Linear Regression to analyze the data. The results exhibited a significant relationship between personality types and emotional intelligence and the three dimensions of burnout. It was indicated that the best predictors for emotional exhaustion were neuroticism and extroversion, for depersonalization were intrapersonal scale of emotional intelligence and agreeableness, and for personal accomplishment were interpersonal scale and conscientiousness. Finally, the results were discussed in the context of teacher burnout.

The relationship between depressive symptoms among female workers and job stress and sleep quality.

PubMed

Cho, Ho-Sung; Kim, Young-Wook; Park, Hyoung-Wook; Lee, Kang-Ho; Jeong, Baek-Geun; Kang, Yune-Sik; Park, Ki-Soo

2013-07-22

Recently, workers' mental health has become important focus in the field of occupational health management. Depression is a psychiatric illness with a high prevalence. The association between job stress and depressive symptoms has been demonstrated in many studies. Recently, studies about the association between sleep quality and depressive symptoms have been reported, but there has been no large-scaled study in Korean female workers. Therefore, this study was designed to investigate the relationship between job stress and sleep quality, and depressive symptoms in female workers. From Mar 2011 to Aug 2011, 4,833 female workers in the manufacturing, finance, and service fields at 16 workplaces in Yeungnam province participated in this study, conducted in combination with a worksite-based health checkup initiated by the National Health Insurance Service (NHIS). In this study, a questionnaire survey was carried out using the Korean Occupational Stress Scale-Short Form(KOSS-SF), Pittsburgh Sleep Quality Index(PSQI) and Center for Epidemiological Studies-Depression Scale(CES-D). The collected data was entered in the system and analyzed using the PASW (version 18.0) program. A correlation analysis, cross analysis, multivariate logistic regression analysis, and hierarchical multiple regression analysis were conducted. Among the 4,883 subjects, 978 subjects (20.0%) were in the depression group. Job stress(OR=3.58, 95% CI=3.06-4.21) and sleep quality(OR=3.81, 95% CI=3.18-4.56) were strongly associated with depressive symptoms. Hierarchical multiple regression analysis revealed that job stress displayed explanatory powers of 15.6% on depression while sleep quality displayed explanatory powers of 16.2%, showing that job stress and sleep quality had a closer relationship with depressive symptoms, compared to the other factors. The multivariate logistic regression analysis yielded odds ratios between the 7 subscales of job stress and depressive symptoms in the range of 1.30-2.72 and the odds ratio for the lack of reward was the highest(OR=2.72, 95% CI=2.32-3.19). In the partial correlation analysis between each of the 7 subscales of sleep quality (PSQI) and depressive symptoms, the correlation coefficient of subjective sleep quality and daytime dysfunction were 0.352 and 0.362, respectively. This study showed that the depressive symptoms of female workers are closely related to their job stress and sleep quality. In particular, the lack of reward and subjective sleep factors are the greatest contributors to depression. In the future, a large-scale study should be performed to augment the current study and to reflect all age groups in a balanced manner. The findings on job stress, sleep, and depression can be utilized as source data to establish standards for mental health management of the ever increasing numbers of female members of the workplace.

A Method of Calculating Functional Independence Measure at Discharge from Functional Independence Measure Effectiveness Predicted by Multiple Regression Analysis Has a High Degree of Predictive Accuracy.

PubMed

Tokunaga, Makoto; Watanabe, Susumu; Sonoda, Shigeru

2017-09-01

Multiple linear regression analysis is often used to predict the outcome of stroke rehabilitation. However, the predictive accuracy may not be satisfactory. The objective of this study was to elucidate the predictive accuracy of a method of calculating motor Functional Independence Measure (mFIM) at discharge from mFIM effectiveness predicted by multiple regression analysis. The subjects were 505 patients with stroke who were hospitalized in a convalescent rehabilitation hospital. The formula "mFIM at discharge = mFIM effectiveness × (91 points - mFIM at admission) + mFIM at admission" was used. By including the predicted mFIM effectiveness obtained through multiple regression analysis in this formula, we obtained the predicted mFIM at discharge (A). We also used multiple regression analysis to directly predict mFIM at discharge (B). The correlation between the predicted and the measured values of mFIM at discharge was compared between A and B. The correlation coefficients were .916 for A and .878 for B. Calculating mFIM at discharge from mFIM effectiveness predicted by multiple regression analysis had a higher degree of predictive accuracy of mFIM at discharge than that directly predicted. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Use of Empirical Estimates of Shrinkage in Multiple Regression: A Caution.

ERIC Educational Resources Information Center

Kromrey, Jeffrey D.; Hines, Constance V.

1995-01-01

The accuracy of four empirical techniques to estimate shrinkage in multiple regression was studied through Monte Carlo simulation. None of the techniques provided unbiased estimates of the population squared multiple correlation coefficient, but the normalized jackknife and bootstrap techniques demonstrated marginally acceptable performance with…

Enhance-Synergism and Suppression Effects in Multiple Regression

ERIC Educational Resources Information Center

Lipovetsky, Stan; Conklin, W. Michael

2004-01-01

Relations between pairwise correlations and the coefficient of multiple determination in regression analysis are considered. The conditions for the occurrence of enhance-synergism and suppression effects when multiple determination becomes bigger than the total of squared correlations of the dependent variable with the regressors are discussed. It…

Psychosocial job factors and biological cardiovascular risk factors in Mexican workers.

PubMed

Garcia-Rojas, Isabel Judith; Choi, BongKyoo; Krause, Niklas

2015-03-01

Psychosocial job factors (PJF) have been implicated in the development of cardiovascular disease. The paucity of data from developing economies including Mexico hampers the development of worksite intervention efforts in those regions. This cross-sectional study of 2,330 Mexican workers assessed PJF (job strain [JS], social support [SS], and job insecurity [JI]) and biological cardiovascular disease risk factors [CVDRF] by questionnaire and on-site physical examinations. Alternative formulations of the JS scales were developed based on factor analysis and literature review. Associations between both traditional and alternative job factor scales with CVDRF were examined in multiple regression models, adjusting for physical workload, and socio-demographic factors. Alternative formulations of the job demand and control scales resulted in substantial changes in effect sizes or statistical significance when compared with the original scales. JS and JI showed hypothesized associations with most CVDRF, but they were inversely associated with diastolic blood pressure and some adiposity measures. SS was mainly protective against CVDRF. Among Mexican workers, alternative PJF scales predicted health outcomes better than traditional scales, and psychosocial stressors were associated with most CVDRF. © 2015 Wiley Periodicals, Inc.

Associations among attitudes, perceived difficulty of learning science, gender, parents' occupation and students' scientific competencies

NASA Astrophysics Data System (ADS)

Chi, ShaoHui; Wang, Zuhao; Liu, Xiufeng; Zhu, Lei

2017-11-01

This study investigated the associations among students' attitudes towards science, students' perceived difficulty of learning science, gender, parents' occupations and their scientific competencies. A sample of 1591 (720 males and 871 females) ninth-grade students from 29 junior high schools in Shanghai completed a scientific competency test and a Likert scale questionnaire. Multiple regression analysis revealed that students' general interest of science, their parents' occupations and perceived difficulty of science significantly associated with their scientific competencies. However, there was no gender gap in terms of scientific competencies.

TV watching, soap opera and happiness.

PubMed

Lu, L; Argyle, M

1993-09-01

One hundred and fourteen subjects reported the amount of time they spent watching television in general, and soap opera in particular. They also completed scales measuring happiness and other personality variables, such as extraversion and cooperativeness. In the multiple regression analysis, having controlled for the demographic variables, watching TV was related to unhappiness, whereas watching soap opera was related to happiness. Discriminant analysis showed that females, higher happiness and extraversion distinguished regular soap watchers (who nevertheless watched little TV in general) from irregular soap watchers (who nevertheless watched a lot of TV in general).

An Effect Size for Regression Predictors in Meta-Analysis

ERIC Educational Resources Information Center

Aloe, Ariel M.; Becker, Betsy Jane

2012-01-01

A new effect size representing the predictive power of an independent variable from a multiple regression model is presented. The index, denoted as r[subscript sp], is the semipartial correlation of the predictor with the outcome of interest. This effect size can be computed when multiple predictor variables are included in the regression model…

Regression Analysis: Legal Applications in Institutional Research

ERIC Educational Resources Information Center

Frizell, Julie A.; Shippen, Benjamin S., Jr.; Luna, Andrew L.

2008-01-01

This article reviews multiple regression analysis, describes how its results should be interpreted, and instructs institutional researchers on how to conduct such analyses using an example focused on faculty pay equity between men and women. The use of multiple regression analysis will be presented as a method with which to compare salaries of…

RAWS II: A MULTIPLE REGRESSION ANALYSIS PROGRAM,

DTIC Science & Technology

This memorandum gives instructions for the use and operation of a revised version of RAWS, a multiple regression analysis program. The program...of preprocessed data, the directed retention of variable, listing of the matrix of the normal equations and its inverse, and the bypassing of the regression analysis to provide the input variable statistics only. (Author)

Incremental Net Effects in Multiple Regression

ERIC Educational Resources Information Center

Lipovetsky, Stan; Conklin, Michael

2005-01-01

A regular problem in regression analysis is estimating the comparative importance of the predictors in the model. This work considers the 'net effects', or shares of the predictors in the coefficient of the multiple determination, which is a widely used characteristic of the quality of a regression model. Estimation of the net effects can be a…

Production of Selected Key Ductile Iron Castings Used in Large-Scale Windmills

NASA Astrophysics Data System (ADS)

Pan, Yung-Ning; Lin, Hsuan-Te; Lin, Chi-Chia; Chang, Re-Mo

Both the optimal alloy design and microstructures that conform to the mechanical properties requirements of selected key components used in large-scale windmills have been established in this study. The target specifications in this study are EN-GJS-350-22U-LT, EN-GJS-350-22U-LT and EN-GJS-700-2U. In order to meet the impact requirement of spec. EN-GJS-350-22U-LT, the Si content should be kept below 1.97%, and also the maximum pearlite content shouldn't exceed 7.8%. On the other hand, Si content below 2.15% and pearlite content below 12.5% were registered for specification EN-GJS-400-18U-LT. On the other hand, the optimal alloy designs that can comply with specification EN-GJS-700-2U include 0.25%Mn+0.6%Cu+0.05%Sn, 0.25%Mn+0.8%Cu+0.01%Sn and 0.45%Mn+0.6%Cu+0.01%Sn. Furthermore, based upon the experimental results, multiple regression analyses have been performed to correlate the mechanical properties with chemical compositions and microstructures. The derived regression equations can be used to attain the optimal alloy design for castings with target specifications. Furthermore, by employing these regression equations, the mechanical properties can be predicted based upon the chemical compositions and microstructures of cast irons.

Using Multiple and Logistic Regression to Estimate the Median WillCost and Probability of Cost and Schedule Overrun for Program Managers

DTIC Science & Technology

2017-03-23

PUBLIC RELEASE; DISTRIBUTION UNLIMITED Using Multiple and Logistic Regression to Estimate the Median Will- Cost and Probability of Cost and... Cost and Probability of Cost and Schedule Overrun for Program Managers Ryan C. Trudelle Follow this and additional works at: https://scholar.afit.edu...afit.edu. Recommended Citation Trudelle, Ryan C., "Using Multiple and Logistic Regression to Estimate the Median Will- Cost and Probability of Cost and

Incremental validity of the Minnesota Multiphasic Personality Inventory-2 and symptom checklist-90-revised with mental health inpatients.

PubMed

Simonds, Elise C; Handel, Richard W; Archer, Robert P

2008-03-01

This study evaluated the incremental validity of scores from the Minnesota Multiphasic Personality Inventory-2 (MMPI-2) and the Symptom Checklist-90-Revised (SCL-90-R) in a sample of mental health inpatients originally published by Archer, Griffin, and Aiduk (1995). The incremental validity of scores from the SCL-90-R primary symptom dimensions and MMPI-2 Clinical, Content, and Restructured Clinical scales was assessed in a sample of 544 mental health inpatients using conceptually related items from the Brief Psychiatric Rating Scale (BPRS) as criteria. A series of hierarchical multiple regressions indicated that scores from the SCL-90-R primary symptom dimensions exhibited limited incremental validity (Mdn DeltaR(2) = .01, range = 0-.01), whereas scores from MMPI-2 scales contributed additional information in the prediction of ratings on all but one BPRS item (Mdn DeltaR( 2) = .08, range = .04-.12).

The relationship between satisfaction with life, ADHD symptoms, and associated problems among university students.

PubMed

Gudjonsson, Gisli H; Sigurdsson, Jon Fridrik; Eyjolfsdottir, Gudrun Agusta; Smari, Jakob; Young, Susan

2009-05-01

To ascertain whether ADHD symptoms, and associated problems, are negatively related to subjective well-being. The Satisfaction With Life Scale (SWLS) was completed by 369 university students, along with the Reasoning & Rehabilitation (R&R) ADHD Training Evaluation (RATE), the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) Scale for current ADHD symptoms, and the Depression Anxiety Stress Scales (DASS). The SWLS was negatively correlated with all the other measures, and the strongest correlations were with the Total RATE score. A multiple regression analysis showed that the variables in the study accounted for 22% and 25% of the variance of the SWLS among males and females, respectively. Among males poor social functioning was the best predictor of dissatisfaction with life, whereas among females it was poor emotional control. Both ADHD symptoms and associated problems are significantly related to poorer satisfaction with life.

Social networks and health-related quality of life: a population based study among older adults.

PubMed

Gallegos-Carrillo, Katia; Mudgal, Jyoti; Sánchez-García, Sergio; Wagner, Fernando A; Gallo, Joseph J; Salmerón, Jorge; García-Peña, Carmen

2009-01-01

To examine the relationship between components of social networks and health-related quality of life (HRQL) in older adults with and without depressive symptoms. Comparative cross-sectional study with data from the cohort study 'Integral Study of Depression', carried out in Mexico City during 2004. The sample was selected through a multi-stage probability design. HRQL was measured with the SF-36. Geriatric Depression Scale (GDS) and the Short Anxiety Screening Test (SAST) determined depressive symptoms and anxiety. T-test and multiple linear regressions were conducted. Older adults with depressive symptoms had the lowest scores in all HRQL scales. A larger network of close relatives and friends was associated with better HRQL on several scales. Living alone did not significantly affect HRQL level, in either the study or comparison group. A positive association between some components of social networks and good HRQL exists even in older adults with depressive symptoms.

THE RELATIONSHIP BETWEEN CULTURAL IDENTITY AND SELF-ESTEEM AMONG CHINESE UYGHUR COLLEGE STUDENTS: THE MEDIATING ROLE OF ACCULTURATION ATTITUDES.

PubMed

Dong, Li; Lin, Chongde; Li, Tsingan; Dou, Donghui; Zhou, Liqing

2015-08-01

Most acculturation research throughout the world has been conducted in immigrant settings. In order to examine the generalizability of the previous conclusions in immigrant settings, the present study tried to explore the relationship between cultural identity and self-esteem and the mediating role of acculturation attitudes in China. Using the cross-sectional design, a total number of 342 Uyghur college students were asked to complete a survey comprising the Multi-Group Ethnic/National Identity Measure-Revised Scale, the Acculturation Attitudes Scale, and the Rosenberg Self-Esteem Scale. Using hierarchical multiple regression, the results indicated that cultural identity was positively correlated with self-esteem. A significant mediation of acculturation was observed between cultural identity and self-esteem. These findings demonstrated the significance of cultural identity and acculturation attitudes in the adaptation of Chinese Uyghur college students, in which integration is an optimal acculturation attitude.

Is there a place for extended assessments in addressing child sexual abuse allegations? How sensitivity and specificity impact professional perspectives.

PubMed

Williams, Javonda; Nelson-Gardell, Debra; Coulborn Faller, Kathleen; Tishelman, Amy; Cordisco-Steele, Linda

2014-01-01

Using data from a survey of perceptions of 932 child welfare professionals about the utility of extended assessments, the researchers constructed a scale to measure respondents' views about sensitivity (ensuring sexually abused children are correctly identified) and specificity (ensuring nonabused children are correctly identified) in child sexual abuse evaluations. On average, respondents scored high (valuing sensitivity) on the sensitivity versus specificity scale. Next, the researchers undertook bivariate analyses to identify independent variables significantly associated with the sensitivity versus specificity scale. Then those variables were entered into a multiple regression. Four independent variables were significantly related to higher sensitivity scores: encountering cases requiring extended assessments, valuing extended assessments among scarce resources, less concern about proving cases in court, and viewing the goal of extended assessments as understanding needs of child and family (adjusted R2 = .34).

Evaluation of the CEAS model for barley yields in North Dakota and Minnesota

NASA Technical Reports Server (NTRS)

Barnett, T. L. (Principal Investigator)

1981-01-01

The CEAS yield model is based upon multiple regression analysis at the CRD and state levels. For the historical time series, yield is regressed on a set of variables derived from monthly mean temperature and monthly precipitation. Technological trend is represented by piecewise linear and/or quadriatic functions of year. Indicators of yield reliability obtained from a ten-year bootstrap test (1970-79) demonstrated that biases are small and performance as indicated by the root mean square errors are acceptable for intended application, however, model response for individual years particularly unusual years, is not very reliable and shows some large errors. The model is objective, adequate, timely, simple and not costly. It considers scientific knowledge on a broad scale but not in detail, and does not provide a good current measure of modeled yield reliability.

Multidimensional Predictors of Fatigue among Octogenarians and Centenarians

PubMed Central

Cho, Jinmyoung; Martin, Peter; Margrett, Jennifer; MacDonald, Maurice; Johnson, Mary Ann; Poon, Leonard W.

2012-01-01

Background Fatigue is a common and frequently observed complaint among older adults. However, knowledge about the nature and correlates of fatigue in old age is very limited. Objective: This study examined the relationship of functional indicators, psychological and situational factors and fatigue for 210 octogenarians and centenarians from the Georgia Centenarian Study. Methods Three indicators of functional capacity (self-rated health, instrumental activities of daily living, physical activities of daily living), two indicators of psychological well-being (positive and negative affect), two indicators of situational factors (social network and social support), and a multidimensional fatigue scale were used. Blocked multiple regression analyses were computed to examine significant factors related to fatigue. In addition, multi-group analysis in structural equation modeling was used to investigate residential differences (i.e., long-term care facilities vs. private homes) in the relationship between significant factors and fatigue. Results Blocked multiple regression analyses indicated that two indicators of functional capacity, self-rated health and instrumental activities of daily living, both positive and negative affect, and social support were significant predictors of fatigue among oldest-old adults. The multiple group analysis in structural equation modeling revealed a significant difference among oldest-old adults based on residential status. Conclusion The results suggest that we should not consider fatigue as merely an unpleasant physical symptom, but rather adopt a perspective that different factors such as psychosocial aspects can influence fatigue in advanced later life. PMID:22094445

Multidimensional predictors of fatigue among octogenarians and centenarians.

PubMed

Cho, Jinmyoung; Martin, Peter; Margrett, Jennifer; MacDonald, Maurice; Johnson, Mary Ann; Poon, Leonard W; Jazwinski, S M; Green, R C; Gearing, M; Woodard, J L; Tenover, J S; Siegler, I C; Rott, C; Rodgers, W L; Hausman, D; Arnold, J; Davey, A

2012-01-01

Fatigue is a common and frequently observed complaint among older adults. However, knowledge about the nature and correlates of fatigue in old age is very limited. This study examined the relationship of functional indicators, psychological and situational factors and fatigue for 210 octogenarians and centenarians from the Georgia Centenarian Study. Three indicators of functional capacity (self-rated health, instrumental activities of daily living, physical activities of daily living), two indicators of psychological well-being (positive and negative affect), two indicators of situational factors (social network and social support), and a multidimensional fatigue scale were used. Blocked multiple regression analyses were computed to examine significant factors related to fatigue. In addition, multi-group analysis in structural equation modeling was used to investigate residential differences (i.e., long-term care facilities vs. private homes) in the relationship between significant factors and fatigue. Blocked multiple regression analyses indicated that two indicators of functional capacity, self-rated health and instrumental activities of daily living, both positive and negative affect, and social support were significant predictors of fatigue among oldest-old adults. The multiple group analysis in structural equation modeling revealed a significant difference among oldest-old adults based on residential status. The results suggest that we should not consider fatigue as merely an unpleasant physical symptom, but rather adopt a perspective that different factors such as psychosocial aspects can influence fatigue in advanced later life. Copyright © 2011 S. Karger AG, Basel.

The relationship between psychosocial maturity and assertiveness in males and females.

PubMed

Goldman, J A; Olczak, P V

1981-02-01

The relationship between psychosocial maturity (psychological health) and assertiveness was investigated in a sample of United States college males and females. Results revealed a moderately high positive relationship between psychosocial maturity (PSM) and self-reported assertiveness on the Rathus and Galassi scales for both sexes. This relationship was slightly stronger (in terms of variance accounted for) for males than females, significant differences being obtained for Intimacy on the Rathus scale and PSM and Intimacy on the Galassi scale. Multiple regression analyses revealed that the personality components most consistently accounting for major portions of the variance in predicting male assertiveness scores on both the Rathus Assertiveness Schedule and the College Self-Expression Scale were Intimacy and Initiative, while in predicting female assertiveness, only Initiative was involved. The findings were related to previous research, recent work on the androgyny construct (instrumental vs. expressive behaviors), and exhortations for increased cooperation between schools of psychotherapy to establish it as a more unified discipline.

Flows, scaling, and the control of moment hierarchies for stochastic chemical reaction networks

NASA Astrophysics Data System (ADS)

Smith, Eric; Krishnamurthy, Supriya

2017-12-01

Stochastic chemical reaction networks (CRNs) are complex systems that combine the features of concurrent transformation of multiple variables in each elementary reaction event and nonlinear relations between states and their rates of change. Most general results concerning CRNs are limited to restricted cases where a topological characteristic known as deficiency takes a value 0 or 1, implying uniqueness and positivity of steady states and surprising, low-information forms for their associated probability distributions. Here we derive equations of motion for fluctuation moments at all orders for stochastic CRNs at general deficiency. We show, for the standard base case of proportional sampling without replacement (which underlies the mass-action rate law), that the generator of the stochastic process acts on the hierarchy of factorial moments with a finite representation. Whereas simulation of high-order moments for many-particle systems is costly, this representation reduces the solution of moment hierarchies to a complexity comparable to solving a heat equation. At steady states, moment hierarchies for finite CRNs interpolate between low-order and high-order scaling regimes, which may be approximated separately by distributions similar to those for deficiency-zero networks and connected through matched asymptotic expansions. In CRNs with multiple stable or metastable steady states, boundedness of high-order moments provides the starting condition for recursive solution downward to low-order moments, reversing the order usually used to solve moment hierarchies. A basis for a subset of network flows defined by having the same mean-regressing property as the flows in deficiency-zero networks gives the leading contribution to low-order moments in CRNs at general deficiency, in a 1 /n expansion in large particle numbers. Our results give a physical picture of the different informational roles of mean-regressing and non-mean-regressing flows and clarify the dynamical meaning of deficiency not only for first-moment conditions but for all orders in fluctuations.

Functional disability and its predictors in systemic sclerosis: a study from the DeSScipher project within the EUSTAR group.

PubMed

Jaeger, Veronika K; Distler, Oliver; Maurer, Britta; Czirják, Laszlo; Lóránd, Veronika; Valentini, Gabriele; Vettori, Serena; Del Galdo, Francesco; Abignano, Giuseppina; Denton, Christopher; Nihtyanova, Svetlana; Allanore, Yannick; Avouac, Jerome; Riemekasten, Gabriele; Siegert, Elise; Huscher, Dörte; Matucci-Cerinic, Marco; Guiducci, Serena; Frerix, Marc; Tarner, Ingo H; Garay Toth, Beata; Fankhauser, Beat; Umbricht, Jörg; Zakharova, Anastasia; Mihai, Carina; Cozzi, Franco; Yavuz, Sule; Hunzelmann, Nicolas; Rednic, Simona; Vacca, Alessandra; Schmeiser, Tim; Riccieri, Valeria; García de la Peña Lefebvre, Paloma; Gabrielli, Armando; Krummel-Lorenz, Brigitte; Martinovic, Duska; Ancuta, Codrina; Smith, Vanessa; Müller-Ladner, Ulf; Walker, Ulrich A

2018-03-01

The multisystem manifestations of SSc can greatly impact patients' quality of life. The aim of this study was to identify factors associated with disability in SSc. SSc patients from the prospective DeSScipher cohort who had completed the scleroderma health assessment questionnaire (SHAQ), a disability score that combines the health assessment questionnaire and five visual analogue scales, were included in this analysis. The effect of factors possibly associated with disability was analysed with multiple linear regressions. The mean SHAQ and HAQ scores of the 944 patients included were 0.87 (s.d. = 0.66) and 0.92 (s.d. = 0.78); 59% of the patients were in the mild to moderate difficulty SHAQ category (0 ⩽ SHAQ < 1), 34% in the moderate to severe disability category (1 ⩽ SHAQ < 2) and 7% in the severe to very severe disability category (2 ⩽ SHAQ ⩽ 3). The means of the visual analogue scales scores were in order of magnitude: overall disease severity (37 mm), RP (31 mm), pulmonary symptoms (24 mm), gastrointestinal symptoms (20 mm) and digital ulcers (19 mm). In multiple regression, the main factors associated with high SHAQ scores were the presence of dyspnoea [modified New York Heart Association (NYHA) class IV (regression coefficient B = 0.62), modified NYHA class III (B = 0.53) and modified NYHA class II (B = 0.21; all vs modified NYHA class I)], FM (B = 0.37), muscle weakness (B = 0.27), digital ulcers (B = 0.20) and gastrointestinal symptoms (oesophageal symptoms, B = 0.16; stomach symptoms, B = 0.15; intestinal symptoms, B = 0.15). SSc patients perceive dyspnoea, pain, digital ulcers, muscle weakness and gastrointestinal symptoms as the main factors driving their level of disability, unlike physicians who emphasize objective measures of disability. © The Author 2017. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com

A hybrid approach to estimating national scale spatiotemporal variability of PM2.5 in the contiguous United States.

PubMed

Beckerman, Bernardo S; Jerrett, Michael; Serre, Marc; Martin, Randall V; Lee, Seung-Jae; van Donkelaar, Aaron; Ross, Zev; Su, Jason; Burnett, Richard T

2013-07-02

Airborne fine particulate matter exhibits spatiotemporal variability at multiple scales, which presents challenges to estimating exposures for health effects assessment. Here we created a model to predict ambient particulate matter less than 2.5 μm in aerodynamic diameter (PM2.5) across the contiguous United States to be applied to health effects modeling. We developed a hybrid approach combining a land use regression model (LUR) selected with a machine learning method, and Bayesian Maximum Entropy (BME) interpolation of the LUR space-time residuals. The PM2.5 data set included 104,172 monthly observations at 1464 monitoring locations with approximately 10% of locations reserved for cross-validation. LUR models were based on remote sensing estimates of PM2.5, land use and traffic indicators. Normalized cross-validated R(2) values for LUR were 0.63 and 0.11 with and without remote sensing, respectively, suggesting remote sensing is a strong predictor of ground-level concentrations. In the models including the BME interpolation of the residuals, cross-validated R(2) were 0.79 for both configurations; the model without remotely sensed data described more fine-scale variation than the model including remote sensing. Our results suggest that our modeling framework can predict ground-level concentrations of PM2.5 at multiple scales over the contiguous U.S.

Relationships between avian richness and landscape structure at multiple scales using multiple landscapes

USGS Publications Warehouse

Mitchell, M.S.; Rutzmoser, S.H.; Wigley, T.B.; Loehle, C.; Gerwin, J.A.; Keyser, P.D.; Lancia, R.A.; Perry, R.W.; Reynolds, C.J.; Thill, R.E.; Weih, R.; White, D.; Wood, P.B.

2006-01-01

Little is known about factors that structure biodiversity on landscape scales, yet current land management protocols, such as forest certification programs, place an increasing emphasis on managing for sustainable biodiversity at landscape scales. We used a replicated landscape study to evaluate relationships between forest structure and avian diversity at both stand and landscape-levels. We used data on bird communities collected under comparable sampling protocols on four managed forests located across the Southeastern US to develop logistic regression models describing relationships between habitat factors and the distribution of overall richness and richness of selected guilds. Landscape models generated for eight of nine guilds showed a strong relationship between richness and both availability and configuration of landscape features. Diversity of topographic features and heterogeneity of forest structure were primary determinants of avian species richness. Forest heterogeneity, in both age and forest type, were strongly and positively associated with overall avian richness and richness for most guilds. Road density was associated positively but weakly with avian richness. Landscape variables dominated all models generated, but no consistent patterns in metrics or scale were evident. Model fit was strong for neotropical migrants and relatively weak for short-distance migrants and resident species. Our models provide a tool that will allow managers to evaluate and demonstrate quantitatively how management practices affect avian diversity on landscapes.

Fire frequency in the Interior Columbia River Basin: Building regional models from fire history data

USGS Publications Warehouse

McKenzie, D.; Peterson, D.L.; Agee, James K.

2000-01-01

Fire frequency affects vegetation composition and successional pathways; thus it is essential to understand fire regimes in order to manage natural resources at broad spatial scales. Fire history data are lacking for many regions for which fire management decisions are being made, so models are needed to estimate past fire frequency where local data are not yet available. We developed multiple regression models and tree-based (classification and regression tree, or CART) models to predict fire return intervals across the interior Columbia River basin at 1-km resolution, using georeferenced fire history, potential vegetation, cover type, and precipitation databases. The models combined semiqualitative methods and rigorous statistics. The fire history data are of uneven quality; some estimates are based on only one tree, and many are not cross-dated. Therefore, we weighted the models based on data quality and performed a sensitivity analysis of the effects on the models of estimation errors that are due to lack of cross-dating. The regression models predict fire return intervals from 1 to 375 yr for forested areas, whereas the tree-based models predict a range of 8 to 150 yr. Both types of models predict latitudinal and elevational gradients of increasing fire return intervals. Examination of regional-scale output suggests that, although the tree-based models explain more of the variation in the original data, the regression models are less likely to produce extrapolation errors. Thus, the models serve complementary purposes in elucidating the relationships among fire frequency, the predictor variables, and spatial scale. The models can provide local managers with quantitative information and provide data to initialize coarse-scale fire-effects models, although predictions for individual sites should be treated with caution because of the varying quality and uneven spatial coverage of the fire history database. The models also demonstrate the integration of qualitative and quantitative methods when requisite data for fully quantitative models are unavailable. They can be tested by comparing new, independent fire history reconstructions against their predictions and can be continually updated, as better fire history data become available.

Tools to Support Interpreting Multiple Regression in the Face of Multicollinearity

PubMed Central

Kraha, Amanda; Turner, Heather; Nimon, Kim; Zientek, Linda Reichwein; Henson, Robin K.

2012-01-01

While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses. PMID:22457655

Tools to support interpreting multiple regression in the face of multicollinearity.

PubMed

Kraha, Amanda; Turner, Heather; Nimon, Kim; Zientek, Linda Reichwein; Henson, Robin K

2012-01-01

While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses.

Impacts of education level and employment status on health-related quality of life in multiple sclerosis patients.

PubMed

Šabanagić-Hajrić, Selma; Alajbegović, Azra

2015-02-01

To evaluate the impacts of education level and employment status on health-related quality of life (HRQoL) in multiple sclerosis patients. This study included 100 multiple sclerosis patients treated at the Department of Neurology, Clinical Center of the University of Sarajevo. Inclusion criteria were the Expanded Disability Status Scale (EDSS) score between 1.0 and 6.5, age between 18 and 65 years, stable disease on enrollment. Quality of life (QoL) was evaluated by the Multiple Sclerosis Quality of Life-54 questionnaire (MSQoL-54). Mann-Whitney and Kruskal-Wallis test were used for comparisons. Linear regression analyses were performed to evaluate prediction value of educational level and employment status in predicting MSQOL-54 physical and mental composite scores. Full employment status had positive impact on physical health (54.85 vs. 37.90; p les than 0.001) and mental health (59.55 vs. 45.90; p les than 0.001) composite scores. Employment status retained its independent predictability for both physical (r(2)=0.105) and mental (r(2)=0.076) composite scores in linear regression analysis. Patients with college degree had slightly higher median value of physical (49.36 vs. 45.30) and mental health composite score (66.74 vs. 55.62) comparing to others, without statistically significant difference. Employment proved to be an important factor in predicting quality of life in multiple sclerosis patients. Higher education level may determine better QOL but without significant predictive value. Sustained employment and development of vocational rehabilitation programs for MS patients living in the country with high unemployment level is an important factor in improving both physical and mental health outcomes in MS patients.

The comparison between several robust ridge regression estimators in the presence of multicollinearity and multiple outliers

NASA Astrophysics Data System (ADS)

Zahari, Siti Meriam; Ramli, Norazan Mohamed; Moktar, Balkiah; Zainol, Mohammad Said

2014-09-01

In the presence of multicollinearity and multiple outliers, statistical inference of linear regression model using ordinary least squares (OLS) estimators would be severely affected and produces misleading results. To overcome this, many approaches have been investigated. These include robust methods which were reported to be less sensitive to the presence of outliers. In addition, ridge regression technique was employed to tackle multicollinearity problem. In order to mitigate both problems, a combination of ridge regression and robust methods was discussed in this study. The superiority of this approach was examined when simultaneous presence of multicollinearity and multiple outliers occurred in multiple linear regression. This study aimed to look at the performance of several well-known robust estimators; M, MM, RIDGE and robust ridge regression estimators, namely Weighted Ridge M-estimator (WRM), Weighted Ridge MM (WRMM), Ridge MM (RMM), in such a situation. Results of the study showed that in the presence of simultaneous multicollinearity and multiple outliers (in both x and y-direction), the RMM and RIDGE are more or less similar in terms of superiority over the other estimators, regardless of the number of observation, level of collinearity and percentage of outliers used. However, when outliers occurred in only single direction (y-direction), the WRMM estimator is the most superior among the robust ridge regression estimators, by producing the least variance. In conclusion, the robust ridge regression is the best alternative as compared to robust and conventional least squares estimators when dealing with simultaneous presence of multicollinearity and outliers.

An improved multiple linear regression and data analysis computer program package

NASA Technical Reports Server (NTRS)

Sidik, S. M.

1972-01-01

NEWRAP, an improved version of a previous multiple linear regression program called RAPIER, CREDUC, and CRSPLT, allows for a complete regression analysis including cross plots of the independent and dependent variables, correlation coefficients, regression coefficients, analysis of variance tables, t-statistics and their probability levels, rejection of independent variables, plots of residuals against the independent and dependent variables, and a canonical reduction of quadratic response functions useful in optimum seeking experimentation. A major improvement over RAPIER is that all regression calculations are done in double precision arithmetic.

The importance of regional models in assessing canine cancer incidences in Switzerland

PubMed Central

Leyk, Stefan; Brunsdon, Christopher; Graf, Ramona; Pospischil, Andreas; Fabrikant, Sara Irina

2018-01-01

Fitting canine cancer incidences through a conventional regression model assumes constant statistical relationships across the study area in estimating the model coefficients. However, it is often more realistic to consider that these relationships may vary over space. Such a condition, known as spatial non-stationarity, implies that the model coefficients need to be estimated locally. In these kinds of local models, the geographic scale, or spatial extent, employed for coefficient estimation may also have a pervasive influence. This is because important variations in the local model coefficients across geographic scales may impact the understanding of local relationships. In this study, we fitted canine cancer incidences across Swiss municipal units through multiple regional models. We computed diagnostic summaries across the different regional models, and contrasted them with the diagnostics of the conventional regression model, using value-by-alpha maps and scalograms. The results of this comparative assessment enabled us to identify variations in the goodness-of-fit and coefficient estimates. We detected spatially non-stationary relationships, in particular, for the variables related to biological risk factors. These variations in the model coefficients were more important at small geographic scales, making a case for the need to model canine cancer incidences locally in contrast to more conventional global approaches. However, we contend that prior to undertaking local modeling efforts, a deeper understanding of the effects of geographic scale is needed to better characterize and identify local model relationships. PMID:29652921

The importance of regional models in assessing canine cancer incidences in Switzerland.

PubMed

Boo, Gianluca; Leyk, Stefan; Brunsdon, Christopher; Graf, Ramona; Pospischil, Andreas; Fabrikant, Sara Irina

2018-01-01

Fitting canine cancer incidences through a conventional regression model assumes constant statistical relationships across the study area in estimating the model coefficients. However, it is often more realistic to consider that these relationships may vary over space. Such a condition, known as spatial non-stationarity, implies that the model coefficients need to be estimated locally. In these kinds of local models, the geographic scale, or spatial extent, employed for coefficient estimation may also have a pervasive influence. This is because important variations in the local model coefficients across geographic scales may impact the understanding of local relationships. In this study, we fitted canine cancer incidences across Swiss municipal units through multiple regional models. We computed diagnostic summaries across the different regional models, and contrasted them with the diagnostics of the conventional regression model, using value-by-alpha maps and scalograms. The results of this comparative assessment enabled us to identify variations in the goodness-of-fit and coefficient estimates. We detected spatially non-stationary relationships, in particular, for the variables related to biological risk factors. These variations in the model coefficients were more important at small geographic scales, making a case for the need to model canine cancer incidences locally in contrast to more conventional global approaches. However, we contend that prior to undertaking local modeling efforts, a deeper understanding of the effects of geographic scale is needed to better characterize and identify local model relationships.

Variables Associated with Communicative Participation in People with Multiple Sclerosis: A Regression Analysis

ERIC Educational Resources Information Center

Baylor, Carolyn; Yorkston, Kathryn; Bamer, Alyssa; Britton, Deanna; Amtmann, Dagmar

2010-01-01

Purpose: To explore variables associated with self-reported communicative participation in a sample (n = 498) of community-dwelling adults with multiple sclerosis (MS). Method: A battery of questionnaires was administered online or on paper per participant preference. Data were analyzed using multiple linear backward stepwise regression. The…

Dysfunctional Metacognitive Beliefs in Body Dysmorphic Disorder

PubMed Central

Zeinodini, Zahra; Sedighi, Sahar; Rahimi, Mandana Baghertork; Noorbakhsh, Simasadat; Esfahani, Sepideh Rajezi

2016-01-01

The present study aims to examine the correlation of body dysmorphic disorder, with metacognitive subscales, metaworry and thought-fusion. The study was conducted in a correlation framework. Sample included 155 high school students in Isfahan, Iran in 2013-2014, gathered through convenience sampling. To gather data about BDD, Yale-Brown Obsessive Compulsive Scale Modified for BDD was applied. Then, Meta Cognitive Questionnaire, Metaworry Questionnaire, and Thought-Fusion Inventory were used to assess metacognitive subscales, metaworry and thought-fusion. Data obtained from this study were analyzed using Pearson correlation and multiple regressions in SPSS 18. Result indicated YBOCS-BDD scores had a significant correlation with scores from MCQ (P<0.05), MWG (P<0.05), and TFI (P<0.05). Also, multiple regressions were run to predict YBOCS from TFI, MWQ, and MCQ-30. These variables significantly predicted YBOCS [F (3,151) =32.393, R2=0.57]. Findings indicated that body dysmorphic disorder was significantly related to metacognitive subscales, metaworry, and thought fusion in high school students in Isfahan, which is in line with previous studies. A deeper understanding of these processes can broaden theory and treatment of BDD, thereby improve the lives of sufferers and potentially protect others from developing this devastating disorder. PMID:26493420

The relationship among self-efficacy, perfectionism and academic burnout in medical school students.

PubMed

Yu, Ji Hye; Chae, Su Jin; Chang, Ki Hong

2016-03-01

The purpose of this study was to examine the relationship among academic self-efficacy, socially-prescribed perfectionism, and academic burnout in medical school students and to determine whether academic self-efficacy had a mediating role in the relationship between perfectionism and academic burnout. A total of 244 first-year and second-year premed medical students and first- to fourth-year medical students were enrolled in this study. As study tools, socially-prescribed perfectionism, academic self-efficacy, and academic burnout scales were utilized. For data analysis, correlation analysis, multiple regression analysis, and hierarchical multiple regression analyses were conducted. Academic burnout had correlation with socially-prescribed perfectionism. It had negative correlation with academic self-efficacy. Socially-prescribed perfectionism and academic self-efficacy had 54% explanatory power for academic burnout. When socially-prescribed perfectionism and academic self-efficacy were simultaneously used as input, academic self-efficacy partially mediated the relationship between socially-prescribed perfectionism and academic burnout. Socially-prescribed perfectionism had a negative effect on academic self-efficacy, ultimately triggering academic burnout. This suggests that it is important to have educational and counseling interventions to improve academic self-efficacy by relieving academic burnout of medical school students.

Can we "predict" long-term outcome for ambulatory transcutaneous electrical nerve stimulation in patients with chronic pain?

PubMed

Köke, Albère J; Smeets, Rob J E M; Perez, Roberto S; Kessels, Alphons; Winkens, Bjorn; van Kleef, Maarten; Patijn, Jacob

2015-03-01

Evidence for effectiveness of transcutaneous electrical nerve stimulation (TENS) is still inconclusive. As heterogeneity of chronic pain patients might be an important factor for this lack of efficacy, identifying factors for a successful long-term outcome is of great importance. A prospective study was performed to identify variables with potential predictive value for 2 outcome measures on long term (6 months); (1) continuation of TENS, and (2) a minimally clinical important pain reduction of ≥ 33%. At baseline, a set of risk factors including pain-related variables, psychological factors, and disability was measured. In a multiple logistic regression analysis, higher patient's expectations, neuropathic pain, no severe pain (< 80 mm visual analogue scale [VAS]) were independently related to long-term continuation of TENS. For the outcome "minimally clinical important pain reduction," the multiple logistic regression analysis indicated that no multisited pain (> 2 pain locations) and intermittent pain were positively and independently associated with a minimally clinical important pain reduction of ≥ 33%. The results showed that factors associated with a successful outcome in the long term are dependent on definition of successful outcome. © 2014 World Institute of Pain.

The relationship among self-efficacy, perfectionism and academic burnout in medical school students

PubMed Central

Yu, Ji Hye; Chae, Su Jin; Chang, Ki Hong

2016-01-01

Purpose: The purpose of this study was to examine the relationship among academic self-efficacy, socially-prescribed perfectionism, and academic burnout in medical school students and to determine whether academic self-efficacy had a mediating role in the relationship between perfectionism and academic burnout. Methods: A total of 244 first-year and second-year premed medical students and first- to fourth-year medical students were enrolled in this study. As study tools, socially-prescribed perfectionism, academic self-efficacy, and academic burnout scales were utilized. For data analysis, correlation analysis, multiple regression analysis, and hierarchical multiple regression analyses were conducted. Results: Academic burnout had correlation with socially-prescribed perfectionism. It had negative correlation with academic self-efficacy. Socially-prescribed perfectionism and academic self-efficacy had 54% explanatory power for academic burnout. When socially-prescribed perfectionism and academic self-efficacy were simultaneously used as input, academic self-efficacy partially mediated the relationship between socially-prescribed perfectionism and academic burnout. Conclusion: Socially-prescribed perfectionism had a negative effect on academic self-efficacy, ultimately triggering academic burnout. This suggests that it is important to have educational and counseling interventions to improve academic self-efficacy by relieving academic burnout of medical school students. PMID:26838568

The impact of green stormwater infrastructure installation on surrounding health and safety.

PubMed

Kondo, Michelle C; Low, Sarah C; Henning, Jason; Branas, Charles C

2015-03-01

We investigated the health and safety effects of urban green stormwater infrastructure (GSI) installments. We conducted a difference-in-differences analysis of the effects of GSI installments on health (e.g., blood pressure, cholesterol and stress levels) and safety (e.g., felonies, nuisance and property crimes, narcotics crimes) outcomes from 2000 to 2012 in Philadelphia, Pennsylvania. We used mixed-effects regression models to compare differences in pre- and posttreatment measures of outcomes for treatment sites (n=52) and randomly chosen, matched control sites (n=186) within multiple geographic extents surrounding GSI sites. Regression-adjusted models showed consistent and statistically significant reductions in narcotics possession (18%-27% less) within 16th-mile, quarter-mile, half-mile (P<.001), and eighth-mile (P<.01) distances from treatment sites and at the census tract level (P<.01). Narcotics manufacture and burglaries were also significantly reduced at multiple scales. Nonsignificant reductions in homicides, assaults, thefts, public drunkenness, and narcotics sales were associated with GSI installation in at least 1 geographic extent. Health and safety considerations should be included in future assessments of GSI programs. Subsequent studies should assess mechanisms of this association.

[Effect of social desirability on dietary intake estimated from a food questionnaire].

PubMed

Barros, Renata; Moreira, Pedro; Oliveira, Bruno

2005-01-01

Self-report of dietary intake could be biased by social thus affecting risk estimates in epidemiological studies. The objective of study was to assess the effect of social desirability on dietary intake from a food frequency questionnaire (FFQ). A convenience sample of 483 Portuguese university students was recruited. Subjects were invited to complete a two-part self-administered questionnaire: the first part included the Marlowe-Crowne Social Desirability Scale (M-CSDS), a physical activity questionnaire and self-reported height and weight; the second part, included a semi-quantitative FFQ validated for Portuguese adults, that should be returned after fulfillment. All subjects completed the first part of the questionnaire and 40.4% returned the FFQ fairly completed. In multiple regression analysis, after adjustment for energy and confounders, social desirability produced a significant positive effect in the estimates of dietary fibre, vitamin C, vitamin E, magnesium and potassium, in both genders. In multiple regression, after adjustment for energy and confounders, social desirability had a significant positive effect in the estimates of vegetable consumption, for both genders, and a negative effect in white bread and beer, for women. Social desirability affected nutritional and food intake estimated from a food frequency questionnaire.

The Impact of Green Stormwater Infrastructure Installation on Surrounding Health and Safety

PubMed Central

Low, Sarah C.; Henning, Jason; Branas, Charles C.

2015-01-01

Objectives. We investigated the health and safety effects of urban green stormwater infrastructure (GSI) installments. Methods. We conducted a difference-in-differences analysis of the effects of GSI installments on health (e.g., blood pressure, cholesterol and stress levels) and safety (e.g., felonies, nuisance and property crimes, narcotics crimes) outcomes from 2000 to 2012 in Philadelphia, Pennsylvania. We used mixed-effects regression models to compare differences in pre- and posttreatment measures of outcomes for treatment sites (n = 52) and randomly chosen, matched control sites (n = 186) within multiple geographic extents surrounding GSI sites. Results. Regression-adjusted models showed consistent and statistically significant reductions in narcotics possession (18%–27% less) within 16th-mile, quarter-mile, half-mile (P < .001), and eighth-mile (P < .01) distances from treatment sites and at the census tract level (P < .01). Narcotics manufacture and burglaries were also significantly reduced at multiple scales. Nonsignificant reductions in homicides, assaults, thefts, public drunkenness, and narcotics sales were associated with GSI installation in at least 1 geographic extent. Conclusions. Health and safety considerations should be included in future assessments of GSI programs. Subsequent studies should assess mechanisms of this association. PMID:25602887

Analyzing the association between fish consumption and osteoporosis in a sample of Chinese men.

PubMed

Li, Xia; Lei, Tao; Tang, Zihui; Dong, Jingcheng

2017-04-19

The main purpose of this study was to estimate the associations between frequency of fish food consumption and osteoporosis (OP) in general Chinese men. We conducted a large-scale, community-based, cross-sectional study to investigate the associations by using self-report questionnaire to access frequency of fish food intake. A total of 1092 men were available for data analysis in this study. Multiple regression models controlling for confounding factors to include frequency of fish food consumption variable were performed to investigate the relationships for OP. Positive correlations between frequency of fish food consumption and T score were reported (β = 0.084, P value = 0.025). Multiple regression analysis indicated that the frequency of fish food consumption was significantly associated with OP (P < 0.05 for model 1 and model 2). The men with high frequency of fish food consumption had a lower prevalence of OP. The findings indicated that frequency of fish food consumption was independently and significantly associated with OP. The prevalence of OP was less frequent in Chinese men preferring fish food habits. ClinicalTrials.gov Identifier: NCT02451397 retrospectively registered 28 May 2015.

Are you interested? A meta-analysis of relations between vocational interests and employee performance and turnover.

PubMed

Van Iddekinge, Chad H; Roth, Philip L; Putka, Dan J; Lanivich, Stephen E

2011-11-01

A common belief among researchers is that vocational interests have limited value for personnel selection. However, no comprehensive quantitative summaries of interests validity research have been conducted to substantiate claims for or against the use of interests. To help address this gap, we conducted a meta-analysis of relations between interests and employee performance and turnover using data from 74 studies and 141 independent samples. Overall validity estimates (corrected for measurement error in the criterion but not for range restriction) for single interest scales were .14 for job performance, .26 for training performance, -.19 for turnover intentions, and -.15 for actual turnover. Several factors appeared to moderate interest-criterion relations. For example, validity estimates were larger when interests were theoretically relevant to the work performed in the target job. The type of interest scale also moderated validity, such that corrected validities were larger for scales designed to assess interests relevant to a particular job or vocation (e.g., .23 for job performance) than for scales designed to assess a single, job-relevant realistic, investigative, artistic, social, enterprising, or conventional (i.e., RIASEC) interest (.10) or a basic interest (.11). Finally, validity estimates were largest when studies used multiple interests for prediction, either by using a single job or vocation focused scale (which tend to tap multiple interests) or by using a regression-weighted composite of several RIASEC or basic interest scales. Overall, the results suggest that vocational interests may hold more promise for predicting employee performance and turnover than researchers may have thought. (c) 2011 APA, all rights reserved.

Calibration of multivariate scatter plots for exploratory analysis of relations within and between sets of variables in genomic research.

PubMed

Graffelman, Jan; van Eeuwijk, Fred

2005-12-01

The scatter plot is a well known and easily applicable graphical tool to explore relationships between two quantitative variables. For the exploration of relations between multiple variables, generalisations of the scatter plot are useful. We present an overview of multivariate scatter plots focussing on the following situations. Firstly, we look at a scatter plot for portraying relations between quantitative variables within one data matrix. Secondly, we discuss a similar plot for the case of qualitative variables. Thirdly, we describe scatter plots for the relationships between two sets of variables where we focus on correlations. Finally, we treat plots of the relationships between multiple response and predictor variables, focussing on the matrix of regression coefficients. We will present both known and new results, where an important original contribution concerns a procedure for the inclusion of scales for the variables in multivariate scatter plots. We provide software for drawing such scales. We illustrate the construction and interpretation of the plots by means of examples on data collected in a genomic research program on taste in tomato.

Self-Regulatory Strategies as Correlates of Physical Activity Behavior in Persons With Multiple Sclerosis.

PubMed

Cederberg, Katie L; Balto, Julia M; Motl, Robert W

2018-05-01

To examine self-regulation strategies as correlates of physical activity in persons with multiple sclerosis (MS). Cross-sectional, or survey, study. University-based research laboratory. Convenience sample of persons with MS (N=68). Not applicable. Exercise Self-Efficacy Scale (EXSE), 12-item Physical Activity Self-Regulation Scale (PASR-12), and Godin Leisure-Time Exercise Questionnaire (GLTEQ). Correlation analyses indicated that GLTEQ scores were positively and significantly associated with overall self-regulation (r=.43), self-monitoring (r=.45), goal-setting (r=.27), reinforcement (r=.30), time management (r=.41), and relapse prevention (r=.53) PASR-12 scores. Regression analyses indicated that relapse prevention (B=5.01; SE B=1.74; β=.51) and self-monitoring (B=3.65; SE B=1.71; β=.33) were unique predictors of physical activity behavior, and relapse prevention demonstrated a significant association with physical activity behavior that was accounted for by EXSE. Our results indicate that self-regulatory strategies, particularly relapse prevention, may be important correlates of physical activity behavior that can inform the design of future behavioral interventions in MS. Published by Elsevier Inc.

Functional competency and cognitive ability in mild Alzheimer's disease: relationship between ADL assessed by a relative/ carer-rated scale and neuropsychological performance.

PubMed

Matsuda, Osamu; Saito, Masahiko

2005-06-01

Alzheimer's disease (AD) is characterized by multiple cognitive deficits and affects functional competency to perform daily activities (ADL). As this may contribute to the patient's overall disability, it is important to identify factors that compromise competency. The relationship between different cognitive domains and functional activities in AD was studied. The functional competency of 73 Japanese AD patients, most with mild dementia, was assessed using a 27-item relative/carer-rating scale covering 7 ADL: managing finances, using transportation, taking precautions, self-care, housekeeping, communication and taking medicine. Cognitive assessment used 16 neuropsychological tests from the Japanese version of the WAIS-R and COGNISTAT, covering 9 cognitive domains: orientation, attention, episodic memory, semantic memory, language, visuoperceptual and construction abilities, computational ability, abstract thinking, and psychomotor speed. Multiple regression analysis by the stepwise method indicated that functional competency could, for the most part, be predicted from test scores for orientation, abstract thinking and psychomotor speed. The results of this study suggest that impairment of these three cognitive domains plays an important role in the functional deterioration of AD.

Geodesic least squares regression for scaling studies in magnetic confinement fusion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Verdoolaege, Geert

In regression analyses for deriving scaling laws that occur in various scientific disciplines, usually standard regression methods have been applied, of which ordinary least squares (OLS) is the most popular. However, concerns have been raised with respect to several assumptions underlying OLS in its application to scaling laws. We here discuss a new regression method that is robust in the presence of significant uncertainty on both the data and the regression model. The method, which we call geodesic least squares regression (GLS), is based on minimization of the Rao geodesic distance on a probabilistic manifold. We demonstrate the superiority ofmore » the method using synthetic data and we present an application to the scaling law for the power threshold for the transition to the high confinement regime in magnetic confinement fusion devices.« less

Predictors of postoperative outcomes of cubital tunnel syndrome treatments using multiple logistic regression analysis.

PubMed

Suzuki, Taku; Iwamoto, Takuji; Shizu, Kanae; Suzuki, Katsuji; Yamada, Harumoto; Sato, Kazuki

2017-05-01

This retrospective study was designed to investigate prognostic factors for postoperative outcomes for cubital tunnel syndrome (CubTS) using multiple logistic regression analysis with a large number of patients. Eighty-three patients with CubTS who underwent surgeries were enrolled. The following potential prognostic factors for disease severity were selected according to previous reports: sex, age, type of surgery, disease duration, body mass index, cervical lesion, presence of diabetes mellitus, Workers' Compensation status, preoperative severity, and preoperative electrodiagnostic testing. Postoperative severity of disease was assessed 2 years after surgery by Messina's criteria which is an outcome measure specifically for CubTS. Bivariate analysis was performed to select candidate prognostic factors for multiple linear regression analyses. Multiple logistic regression analysis was conducted to identify the association between postoperative severity and selected prognostic factors. Both bivariate and multiple linear regression analysis revealed only preoperative severity as an independent risk factor for poor prognosis, while other factors did not show any significant association. Although conflicting results exist regarding prognosis of CubTS, this study supports evidence from previous studies and concludes early surgical intervention portends the most favorable prognosis. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

[A study of factors influenced by self-efficacy for exercise among community-dwelling elderly men in urban areas].

PubMed

Takai, Itsushi

2012-01-01

It is important to promote self-efficacy for exercise for developing exercise habit. The purpose of this study was to investigate factors influenced by self-efficacy for exercise among community-dwelling elderly men in urban areas. The subjects were 69 elderly men (mean age of 74.2±2.0 SD) who had given approval for participation in the study. We examined the following factors: family situation, history of falls, frequency of going out, stage model of a change, self-efficacy for exercise, fall efficacy scale (FES), geriatric depression scale (GDS), subjective health, functional ability and motor function (5 m walking time, chair stand test-5times). Analysis of variance was used to assess a stage model of a change differences in self-efficacy for exercise and other measures. Correlation analysis and multiple regression analysis were performed to determine the relationships between self-efficacy for exercise and other measures. We found that self-efficacy of exercise, FES, GDS (p<0.01) and CST (p<0.05) vary depending on the stage model of change. Self-efficacy for exercise was found to correlate with psychological factors and functional ability (|r|=0.47-0.67). Multiple regression analysis revealed that the independent factors related to self-efficacy for exercise were FES and GDS. FES and GDS were found to be significant and independent predictors of self-efficacy for exercise in community-dwelling elderly men in urban areas. We should consider not only the approach based on behavioral science but also mental support for depression and fear of falling to promote exercise self-efficacy.

[A Correlational Study of the Recovery Process in Patients With Mental Illness].

PubMed

Huang, Yao-Hui; Lin, Yao-Yu; Lee, Shih-Kai; Lee, Ming-Feng; Lin, Ching-Lan Esther

2018-04-01

The ideology of recovery addresses the autonomy of patients with mental illness and their ability to reconstruct a normal life. Empirical knowledge of this process of recovery and related factors remains unclear. To assess the process of recovery and related factors in patients with mental illness. This cross-sectional, correlational study was conducted on a convenience sample in a psychiatric hospital. Two-hundred and fifty patients with mental illness were recruited and were assessed using 3 instruments: Questionnaire about the Process of Recovery (QPR), Perceived Psychiatric Stigma Scale (PPSS), and Personal and Social Performance Scale (PSP). Data were analyzed using descriptive statistics, χ 2 , analysis of variance, and multiple linear regression analysis. Most of the participants were male, middle-aged, unmarried, educated to the senior high school level, employed, receiving home-care treatment, and diagnosed with schizophrenia. Those who were unemployed, living in a community rehabilitative house, and living in the community, respectively, earned relatively higher recovery scores (p < .05). The total scores of QPR and the 3 subscales were negatively correlated with PPSS (p < .01) and positively correlated with PSPS (p < .01; p < .05). Multiple regression analysis indicated that the factors of education, employment, having received community rehabilitative models, and stigma, respectively, significantly explained the recovery capacity of patients with mental illness. Community psychiatric nurses should provide care to help employed patients adapt to stresses in the workplace, strengthen their stigma-coping strategies, and promote public awareness of mental health issues by increasing public knowledge and acceptance of mental illness in order to minimize patient-perceived stigma and facilitate their recovery.

Predictors of psychological distress in low-income populations of Montreal.

PubMed

Caron, Jean; Latimer, Eric; Tousignant, Michel

2007-01-01

THEORETICAL PERSPECTIVE: Many epidemiologic studies agree that low-income populations are the groups most vulnerable to mental health problems. However, not all people in economic difficulty show symptoms, and it appears that having a social support network plays a role in protecting against the chronic stress resulting from conditions such as poverty. The aim of the study is to clarify the relative contribution of social support to the mental health of low-income populations in two neighbourhoods in the southwest of Montreal: Pointe-Saint Charles and Saint-Henri. A random sample of 416 social assistance recipients in southwest Montreal and another sample of 112 people, drawn at random from the general population, were interviewed. The psychological distress scale used was the Indice de détresse psychologique--Enquête Santê Quêbec (IDPESQ). The availability of social support components was assessed by using the Social Provisions Scale. Data were collected during interviews in the respondents' homes. Social support measures were entered into a multidimensional model including many variables identified as being associated with mental health. Multiple regression analysis identified the best predictors of psychological distress for the low-income population. Among the 30 variables included in a multiple regression analysis, emotional support and the presence of persons perceived as stressful together accounted for most of the variance in distress predicted by the model. Although younger people, people experiencing food insecurity and people with poorer numeracy show a higher level of distress, these variables make a fairly marginal contribution compared with that of social relations.

Risk factors and mediating pathways of loneliness and social support in community-dwelling older adults.

PubMed

Schnittger, Rebecca I B; Wherton, Joseph; Prendergast, David; Lawlor, Brian A

2012-01-01

To develop biopsychosocial models of loneliness and social support thereby identifying their key risk factors in an Irish sample of community-dwelling older adults. Additionally, to investigate indirect effects of social support on loneliness through mediating risk factors. A total of 579 participants (400 females; 179 males) were given a battery of biopsychosocial assessments with the primary measures being the De Jong Gierveld Loneliness Scale and the Lubben Social Network Scale along with a broad range of secondary measures. Bivariate correlation analyses identified items to be included in separate psychosocial, cognitive, biological and demographic multiple regression analyses. The resulting model items were then entered into further multiple regression analyses to obtain overall models. Following this, bootstrapping mediation analyses was conducted to examine indirect effects of social support on the subtypes (emotional and social) of loneliness. The overall model for (1) emotional loneliness included depression, neuroticism, perceived stress, living alone and accommodation type, (2) social loneliness included neuroticism, perceived stress, animal naming and number of grandchildren and (3) social support included extraversion, executive functioning (Trail Making Test B-time), history of falls, age and whether the participant drives or not. Social support influenced emotional loneliness predominantly through indirect means, while its effect on social loneliness was more direct. These results characterise the biopsychosocial risk factors of emotional loneliness, social loneliness and social support and identify key pathways by which social support influences emotional and social loneliness. These findings highlight issues with the potential for consideration in the development of targeted interventions.

The influence of family adaptability and cohesion on anxiety and depression of terminally ill cancer patients.

PubMed

Park, Young-Yoon; Jeong, Young-Jin; Lee, Junyong; Moon, Nayun; Bang, Inho; Kim, Hyunju; Yun, Kyung-Sook; Kim, Yong-I; Jeon, Tae-Hee

2018-01-01

This study investigated the effect of family members on terminally ill cancer patients by measuring the relationship of the presence of the family caregivers, visiting time by family and friends, and family adaptability and cohesion with patient's anxiety and depression. From June, 2016 to March, 2017, 100 terminally ill cancer patients who were admitted to a palliative care unit in Seoul, South Korea, were surveyed, and their medical records were reviewed. The Korean version of the Family Adaptability and Cohesion Evaluation Scales III and Hospital Anxiety-Depression Scale was used. Chi-square and multiple logistic regression analyses were used. The results of the chi-square analysis showed that the presence of family caregivers and family visit times did not have statistically significant effects on anxiety and depression in terminally ill cancer patients. In multiple logistic regression, when adjusted for age, sex, ECOG PS, and the monthly average income, the odds ratios (ORs) of the low family adaptability to anxiety and depression were 2.4 (1.03-5.83) and 5.4 (1.10-26.87), respectively. The OR of low family cohesion for depression was 5.4 (1.10-27.20) when adjusted for age, sex, ECOG PS, and monthly average household income. A higher family adaptability resulted in a lower degree of anxiety and depression in terminally ill cancer patients. The higher the family cohesion, the lower the degree of depression in the patient. The presence of the family caregiver and the visiting time by family and friends did not affect the patient's anxiety and depression.

A fuzzy-logic-based model to predict biogas and methane production rates in a pilot-scale mesophilic UASB reactor treating molasses wastewater.

PubMed

Turkdogan-Aydinol, F Ilter; Yetilmezsoy, Kaan

2010-10-15

A MIMO (multiple inputs and multiple outputs) fuzzy-logic-based model was developed to predict biogas and methane production rates in a pilot-scale 90-L mesophilic up-flow anaerobic sludge blanket (UASB) reactor treating molasses wastewater. Five input variables such as volumetric organic loading rate (OLR), volumetric total chemical oxygen demand (TCOD) removal rate (R(V)), influent alkalinity, influent pH and effluent pH were fuzzified by the use of an artificial intelligence-based approach. Trapezoidal membership functions with eight levels were conducted for the fuzzy subsets, and a Mamdani-type fuzzy inference system was used to implement a total of 134 rules in the IF-THEN format. The product (prod) and the centre of gravity (COG, centroid) methods were employed as the inference operator and defuzzification methods, respectively. Fuzzy-logic predicted results were compared with the outputs of two exponential non-linear regression models derived in this study. The UASB reactor showed a remarkable performance on the treatment of molasses wastewater, with an average TCOD removal efficiency of 93 (+/-3)% and an average volumetric TCOD removal rate of 6.87 (+/-3.93) kg TCOD(removed)/m(3)-day, respectively. Findings of this study clearly indicated that, compared to non-linear regression models, the proposed MIMO fuzzy-logic-based model produced smaller deviations and exhibited a superior predictive performance on forecasting of both biogas and methane production rates with satisfactory determination coefficients over 0.98. 2010 Elsevier B.V. All rights reserved.

The effect of heartburn and acid reflux on the severity of nausea and vomiting of pregnancy

PubMed Central

Gill, Simerpal Kaur; Maltepe, Caroline; Koren, Gideon

2009-01-01

BACKGROUND: Heartburn (HB) and acid reflux (RF) in the non-pregnant population can cause nausea and vomiting; therefore, it is plausible that in women with nausea and vomiting of pregnancy (NVP), HB/RF may increase the severity of symptoms. OBJECTIVE: To determine whether HB/RF during pregnancy contribute to increased severity of NVP. METHODS: A prospectively collected cohort of women who were experiencing NVP and HB, RF or both (n=194) was studied. The Pregnancy-Unique Quantification of Emesis and Nausea (PUQE) scale and its Well-being scale was used to compare the severity of the study cohort’s symptoms. This cohort was compared with a group of women experiencing NVP but no HB/RF (n=188). Multiple linear regression was used to control for the effects of confounding factors. RESULTS: Women with HB/RF reported higher PUQE scores (9.6±2.6) compared with controls (8.9±2.6) (P=0.02). Similarly, Well-being scores for women experiencing HB/RF were lower (4.3±2.1) compared with controls (4.9±2.0) (P=0.01). Multiple linear regression analysis demonstrated that increased PUQE scores (P=0.003) and decreased Well-being scores (P=0.005) were due to the presence of HB/RF as opposed to confounding factors such as pre-existing gastrointestinal conditions/symptoms, hyperemesis gravidarum in previous pregnancies and comorbidities. CONCLUSION: The present cohort study is the first to demonstrate that HB/RF are associated with increased severity of NVP. Managing HB/RF may improve the severity of NVP. PMID:19373420

Association of depression and pain interference with disease-management self-efficacy in community-dwelling individuals with spinal cord injury.

PubMed

Pang, Marco Y C; Eng, Janice J; Lin, Kwan-Hwa; Tang, Pei-Fang; Hung, Chihya; Wang, Yen-Ho

2009-11-01

To determine factors influencing disease-management self-efficacy in individuals with spinal cord injury. A cross-sectional study. Forty-nine community-dwelling individuals with chronic spinal cord injury (mean age 44 years) participated in the study. Each subject was evaluated for disease-management self-efficacy (Self-efficacy for Managing Chronic Disease), depression (10-item Center for Epidemiologic Studies Depression Scale), pain interference (Pain Interference Scale), and availability of support (Interpersonal Support Evaluation List short form). Multiple regression analysis was performed to determine the relative contributions of these factors to disease-management self-efficacy. The mean disease-management self-efficacy score was 6.5 out of 10 (standard deviation 1.6). Bivariate correlation analysis showed that higher self-efficacy was significantly correlated with longer time since injury (r = 0.367, p = 0.010), better social support (r = 0.434, p = 0.002), lower pain interference (r = -0.589, p <0.001), and less severe depressive symptoms (r=-0.463, p=0.001). In multiple regression analysis, only lower pain interference and less severe depressive symptoms were significantly associated with higher disease-management self-efficacy (F 4,44=10.249, R2=0.482, p<0.001). Disease-management self-efficacy is suboptimal in many community-living people with spinal cord injury. This research suggests that rehabilitation of patients with spinal cord injury should include self-efficacy-enhancing strategies. Alleviation of depressive symptoms and pain self-management may be important for improving disease-management self-efficacy in this population, but this requires further study.

Attitudes Toward Obese Persons and Weight Locus of Control in Chinese Nurses: A Cross-sectional Survey.

PubMed

Wang, Yan; Ding, Ye; Song, Daoping; Zhu, Daqiao; Wang, Jianrong

2016-01-01

Obese individuals frequently experience weight-related bias or discrimination-even in healthcare settings. Although obesity bias has been associated with several demographic factors, little is known about the association of weight locus of control with bias against overweight persons or about weight bias among Chinese health professionals. The aim of the study was to examine attitudes toward obese patients in a sample of Chinese registered nurses (RNs) and the relationship between weight bias and nurses' weight locus of control. RNs working in nine community health service centers across Shanghai, China, answered three self-report questionnaires: The Attitudes Toward Obese Persons Scale (ATOP), the External Weight Locus of Control Subscale (eWLOC) from the Dieting Belief Scale, and a sociodemographic profile. Hierarchical, stepwise, multiple regression was used to predict ATOP scores. From among 385 invited, a total of 297 RNs took part in the study (77.1% response rate). Participants scored an average of 71.04 on the ATOP, indicating slightly positive attitudes toward obese persons, and 30.08 on the eWLOC, indicating a belief in the uncontrollability of body weight. Using hierarchical, stepwise, multiple regression, two predictors of ATOP scores were statistically significant (eWLOC scores and status as a specialist rather than generalist nurse), but explained variance was low. Chinese RNs seemed to have relatively neutral or even slightly positive attitudes toward obese persons. Those nurses who believed that obesity was beyond the individual's control or worked in specialties were more likely to have positive attitudes toward obese people. Improved understanding of the comprehensive etiology of obesity is needed.

Inverse Association between Air Pressure and Rheumatoid Arthritis Synovitis

PubMed Central

Furu, Moritoshi; Nakabo, Shuichiro; Ohmura, Koichiro; Nakashima, Ran; Imura, Yoshitaka; Yukawa, Naoichiro; Yoshifuji, Hajime; Matsuda, Fumihiko; Ito, Hiromu; Fujii, Takao; Mimori, Tsuneyo

2014-01-01

Rheumatoid arthritis (RA) is a bone destructive autoimmune disease. Many patients with RA recognize fluctuations of their joint synovitis according to changes of air pressure, but the correlations between them have never been addressed in large-scale association studies. To address this point we recruited large-scale assessments of RA activity in a Japanese population, and performed an association analysis. Here, a total of 23,064 assessments of RA activity from 2,131 patients were obtained from the KURAMA (Kyoto University Rheumatoid Arthritis Management Alliance) database. Detailed correlations between air pressure and joint swelling or tenderness were analyzed separately for each of the 326 patients with more than 20 assessments to regulate intra-patient correlations. Association studies were also performed for seven consecutive days to identify the strongest correlations. Standardized multiple linear regression analysis was performed to evaluate independent influences from other meteorological factors. As a result, components of composite measures for RA disease activity revealed suggestive negative associations with air pressure. The 326 patients displayed significant negative mean correlations between air pressure and swellings or the sum of swellings and tenderness (p = 0.00068 and 0.00011, respectively). Among the seven consecutive days, the most significant mean negative correlations were observed for air pressure three days before evaluations of RA synovitis (p = 1.7×10−7, 0.00027, and 8.3×10−8, for swellings, tenderness and the sum of them, respectively). Standardized multiple linear regression analysis revealed these associations were independent from humidity and temperature. Our findings suggest that air pressure is inversely associated with synovitis in patients with RA. PMID:24454853

Attitudes toward teen mothers among nursing students and psychometric evaluation of Positivity Toward Teen Mothers scale.

PubMed

Kim, Son Chae; Burke, Leanne; Sloan, Chris; Barnett, Shannon

2013-09-01

To prepare future nurses who can deliver high quality nursing care to teen mothers, a better understanding of the nursing students' perception of teen mothers is needed. A descriptive cross-sectional study was conducted among 228 nursing students to evaluate the psychometric properties of the Positivity Toward Teen Mothers (PTTM) scale, to explore nursing students' general empathy and attitudes toward teen mothers, and to investigate the predictors of nursing students' attitudes toward teen mothers. Principal component factor analysis with varimax rotation resulted in a 19-item PTTM-Revised scale with Non-judgmental and Supportive subscales. Cronbach's alphas for the subscales were 0.84 and 0.69, respectively, and 0.87 for the total scale. Simultaneous multiple regression models showed that general empathy and having a teen mother in the family or as an acquaintance were significant predictors of positive attitudes toward teen mothers, whereas age was a significant negative predictor. The PTTM-Revised scale is a promising instrument for assessing attitudes toward teen mothers. Copyright © 2012 Elsevier Ltd. All rights reserved.

Suicide Prevention: College Students' Intention to Intervene.

PubMed

Aldrich, Rosalie S

2017-07-03

The objective of this article was to examine college students' intention to intervene with a suicidal individual and examine the Willingness to Intervene against Suicide questionnaire (WIS). College students (n = 1065) completed an online questionnaire about their attitudes, subjective norms, and perceived behavioral control regarding suicide and suicide intervention as well as their intention to intervene with a suicidal individual. The data were analyzed using confirmatory factor analysis, reliability analysis, and multiple regression. It was found that the WIS significantly predicted intention to intervene with a suicidal individual. The WIS was internally consistent with adequate goodness-of-fit indices for three of the four sub-scales. The WIS is an effective tool for predicting intention to intervene; however, the subjective norms sub-scale should be revised to improve the model.

Examining the Associations Among Home-School Dissonance, Amotivation, and Classroom Disruptive Behavior for Urban High School Students.

PubMed

Brown-Wright, Lynda; Tyler, Kenneth M; Graves, Scott L; Thomas, Deneia; Stevens-Watkins, Danelle; Mulder, Shambra

2013-01-01

The current study examined the association among home-school dissonance, amotivation, and classroom disruptive behavior among 309 high school juniors and seniors at two urban high schools in the Southern region of the country. Students completed two subscales of the Patterns of Learning Activities Scales (PALS) and one subscale of the Academic Motivation Scale (AMS). ANCOVA analyses revealed significant differences in classroom disruptive behaviors for the gender independent variable. Controlling for gender in the multiple hierarchical regression analyses, it was revealed that home-school dissonance significantly predicted both amotivation and classroom disruptive behavior. In addition, a Sobel mediation analysis showed that amotivation was a significant mediator of the association between home-school dissonance and classroom disruptive behavior. Findings and limitations are discussed.

Examining the Associations Among Home–School Dissonance, Amotivation, and Classroom Disruptive Behavior for Urban High School Students

PubMed Central

Brown-Wright, Lynda; Tyler, Kenneth M.; Graves, Scott L.; Thomas, Deneia; Stevens-Watkins, Danelle; Mulder, Shambra

2015-01-01

The current study examined the association among home–school dissonance, amotivation, and classroom disruptive behavior among 309 high school juniors and seniors at two urban high schools in the Southern region of the country. Students completed two subscales of the Patterns of Learning Activities Scales (PALS) and one subscale of the Academic Motivation Scale (AMS). ANCOVA analyses revealed significant differences in classroom disruptive behaviors for the gender independent variable. Controlling for gender in the multiple hierarchical regression analyses, it was revealed that home–school dissonance significantly predicted both amotivation and classroom disruptive behavior. In addition, a Sobel mediation analysis showed that amotivation was a significant mediator of the association between home–school dissonance and classroom disruptive behavior. Findings and limitations are discussed. PMID:27081213

Examining the relationship between authenticity and self-handicapping.

PubMed

Akin, Ahmet; Akin, Umran

2014-12-01

Self-handicapping includes strategies of externalization in which people excuse failure and internalize success, but which also prevents them from behaving in an authentic way. The goal was to investigate the relation of authenticity with self-handicapping. The study was conducted with 366 university students (176 men, 190 women; M age = 20.2 yr.). Participants completed the Turkish version of the Authenticity Scale and the Self-handicapping Scale. Self-handicapping was correlated positively with two factors of authenticity, accepting external influence and self-alienation, and negatively with the authentic living factor. A multiple regression analysis indicated that self-handicapping was predicted positively by self-alienation and accepting external influence and negatively by authentic living, accounting for 21% of the variance collectively. These results demonstrated the negative association of authenticity with self-handicapping.

The Geometry of Enhancement in Multiple Regression

ERIC Educational Resources Information Center

Waller, Niels G.

2011-01-01

In linear multiple regression, "enhancement" is said to occur when R[superscript 2] = b[prime]r greater than r[prime]r, where b is a p x 1 vector of standardized regression coefficients and r is a p x 1 vector of correlations between a criterion y and a set of standardized regressors, x. When p = 1 then b [is congruent to] r and…

Burnout, stress and satisfaction among Australian and New Zealand radiation oncology trainees.

PubMed

Leung, John; Rioseco, Pilar

2017-02-01

To evaluate the incidence of burnout among radiation oncology trainees in Australia and New Zealand and the stress and satisfaction factors related to burnout. A survey of trainees was conducted in mid-2015. There were 42 Likert scale questions on stress, 14 Likert scale questions on satisfaction and the Maslach Burnout Inventory-Human Services Survey assessed burnout. A principal component analysis identified specific stress and satisfaction areas. Categorical variables for the stress and satisfaction factors were computed. Associations between respondent's characteristics and stress and satisfaction subscales were examined by independent sample t-tests and analysis of variance. Effect sizes were calculated using Cohens's d when significant mean differences were observed. This was also done for respondent characteristics and the three burnout subscales. Multiple regression analyses were performed. The response rate was 81.5%. The principal component analysis for stress identified five areas: demands on time, professional development/training, delivery demands, interpersonal demands and administration/organizational issues. There were no significant differences by demographic group or area of interest after P-values were adjusted for the multiple tests conducted. The principal component analysis revealed two satisfaction areas: resources/professional activities and value/delivery of services. There were no significant differences by demographic characteristics or area of interest in the level of satisfaction after P-values were adjusted for the multiple tests conducted. The burnout results revealed 49.5% of respondents scored highly in emotional exhaustion and/or depersonalization and 13.1% had burnout in all three measures. Multiple regression analysis revealed the stress subscales 'demands on time' and 'interpersonal demands' were associated with emotional exhaustion. 'Interpersonal demands' was also associated with depersonalization and correlated negatively with personal accomplishment. The satisfaction of value/delivery of services subscale was associated with higher levels of personal accomplishment. There is a significant level of burnout among radiation oncology trainees in Australia and New Zealand. Further work addressing intervention would be appropriate to reduce levels of burnout. © 2016 The Authors. Journal of Medical Imaging and Radiation Oncology published by John Wiley & Sons Australia, Ltd on behalf of The Royal Australian and New Zealand College of Radiologists.

Herbarium specimens can reveal impacts of climate change on plant phenology; a review of methods and applications.

PubMed

Jones, Casey A; Daehler, Curtis C

2018-01-01

Studies in plant phenology have provided some of the best evidence for large-scale responses to recent climate change. Over the last decade, more than thirty studies have used herbarium specimens to analyze changes in flowering phenology over time, although studies from tropical environments are thus far generally lacking. In this review, we summarize the approaches and applications used to date. Reproductive plant phenology has primarily been analyzed using two summary statistics, the mean flowering day of year and first-flowering day of year, but mean flowering day has proven to be a more robust statistic. Two types of regression models have been applied to test for associations between flowering, temperature and time: flowering day regressed on year and flowering day regressed on temperature. Most studies analyzed the effect of temperature by averaging temperatures from three months prior to the date of flowering. On average, published studies have used 55 herbarium specimens per species to characterize changes in phenology over time, but in many cases fewer specimens were used. Geospatial grid data are increasingly being used for determining average temperatures at herbarium specimen collection locations, allowing testing for finer scale correspondence between phenology and climate. Multiple studies have shown that inferences from herbarium specimen data are comparable to findings from systematically collected field observations. Understanding phenological responses to climate change is a crucial step towards recognizing implications for higher trophic levels and large-scale ecosystem processes. As herbaria are increasingly being digitized worldwide, more data are becoming available for future studies. As temperatures continue to rise globally, herbarium specimens are expected to become an increasingly important resource for analyzing plant responses to climate change.

[Factors associated with activities of daily living (ADL) in independently living elderly persons in a community: a baseline examination of a large scale cohort study, Fujiwara-kyo study].

PubMed

Komatsu, Masayo; Nezu, Satoko; Tomioka, Kimiko; Hazaki, Kan; Harano, Akihiro; Morikawa, Masayuki; Takagi, Masahiro; Yamada, Masahiro; Matsumoto, Yoshitaka; Iwamoto, Junko; Ishizuka, Rika; Saeki, Keigo; Okamoto, Nozomi; Kurumatani, Norio

2013-01-01

To investigate factors associated with activities of daily living in independently living elderly persons in a community. The potential subjects were 4,472 individuals aged 65 years and older who voluntarily participated in a large cohort study, the Fujiwara-kyo study. We used self-administered questionnaires consisting of an activities of daily living (ADL) questionnaire with the Physical Fitness Test established by the Ministry of Education, Culture, Sports, Science and Technology (12 ADL items) to determine the index of higher-level physical independence, demographics, Geriatric Depression Scale, and so on. Mini-mental state examination, measurement of physical fitness, and blood tests were also carried out. A lower ADL level was defined as having a total score of the 12 ADL items (range, 12-36 points) that was below the first quartile of a total score for all the subjects. Factors associated with a low ADL level were examined by multiple logistic regression. A total of 4,198 remained as subjects for analysis. The male, female and 5-year-old groups showed significant differences in the median score of 12 ADL items between any two groups. The highest odds ratio among factors associated with lower ADL level by multiple logistic regression with mutually adjusted independent variables was 4.49 (95%CI: 2.82-7.17) in the groups of "very sharp pain" or "strong pain" during the last month. Low physical ability, self-awareness of limb weakness, a BMI of over 25, low physical activity, cerebrovascular disorder, depression, low cognitive function, unable "to see normally", unable "to hear someone", "muscle, bone and joint pain" were independently associated with lower ADL level. Multiple factors are associated with lower ADL level assessed on the basis of the 12 ADL items.

Advanced statistics: linear regression, part I: simple linear regression.

PubMed

Marill, Keith A

2004-01-01

Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

Personality factors and weight preoccupation: a continuum approach to the association between eating disorders and personality disorders.

PubMed

Davis, C; Claridge, G; Cerullo, D

1997-01-01

Evidence shows a high comorbidity of eating disorders and some forms of personality disorder. Adopting a dimensional approach to both, our study explored their connection among a non-clinical sample. 191 young women completed personality scales of general neuroticism, and of borderline, schizotypal, obsessive-compulsive, and narcissistic (both adjustive and maladaptive) traits. Weight preoccupation (WP), as a normal analogue of eating disorders, was assessed with scales from the Eating Disorder Inventory, and height and weight measured. The data were analysed with multiple regression techniques, with WP as the dependent variable. In low to normal weight subjects, after controlling for the significant influence of body mass, the specific predictors of WP in the regression model were borderline personality and maladaptive narcissism, in the positive direction, and adjustive narcissism and obsessive-compulsiveness in the negative direction. In heavier women, narcissism made no contribution--nor, more significantly, did body mass. Patterns of association between eating pathology and personality disorder, especially borderline and narcissism, can be clearly mapped across to personality traits in the currently non-clinical population. This finding has important implications for understanding dynamics of, and identifying individuals at risk for, eating disorders.

The Protective Role of Resilience in Attenuating Emotional Distress and Aggression Associated with Early-life Stress in Young Enlisted Military Service Candidates.

PubMed

Kim, Joohan; Seok, Jeong-Ho; Choi, Kang; Jon, Duk-In; Hong, Hyun Ju; Hong, Narei; Lee, Eunjeong

2015-11-01

Early life stress (ELS) may induce long-lasting psychological complications in adulthood. The protective role of resilience against the development of psychopathology is also important. The purpose of this study was to investigate the relationships among ELS, resilience, depression, anxiety, and aggression in young adults. Four hundred sixty-one army inductees gave written informed consent and participated in this study. We assessed psychopathology using the Korea Military Personality Test, ELS using the Childhood Abuse Experience Scale, and resilience with the resilience scale. Analyses of variance, correlation analyses, and hierarchical multiple linear regression analyses were conducted for statistical analyses. The regression model explained 35.8%, 41.0%, and 23.3% of the total variance in the depression, anxiety, and aggression indices, respectively. We can find that even though ELS experience is positively associated with depression, anxiety, and aggression, resilience may have significant attenuating effect against the ELS effect on severity of these psychopathologies. Emotion regulation showed the most beneficial effect among resilience factors on reducing severity of psychopathologies. To improve mental health for young adults, ELS assessment and resilience enhancement program should be considered.

The Protective Role of Resilience in Attenuating Emotional Distress and Aggression Associated with Early-life Stress in Young Enlisted Military Service Candidates

PubMed Central

Kim, Joohan; Choi, Kang; Jon, Duk-In; Hong, Hyun Ju; Hong, Narei; Lee, Eunjeong

2015-01-01

Early life stress (ELS) may induce long-lasting psychological complications in adulthood. The protective role of resilience against the development of psychopathology is also important. The purpose of this study was to investigate the relationships among ELS, resilience, depression, anxiety, and aggression in young adults. Four hundred sixty-one army inductees gave written informed consent and participated in this study. We assessed psychopathology using the Korea Military Personality Test, ELS using the Childhood Abuse Experience Scale, and resilience with the resilience scale. Analyses of variance, correlation analyses, and hierarchical multiple linear regression analyses were conducted for statistical analyses. The regression model explained 35.8%, 41.0%, and 23.3% of the total variance in the depression, anxiety, and aggression indices, respectively. We can find that even though ELS experience is positively associated with depression, anxiety, and aggression, resilience may have significant attenuating effect against the ELS effect on severity of these psychopathologies. Emotion regulation showed the most beneficial effect among resilience factors on reducing severity of psychopathologies. To improve mental health for young adults, ELS assessment and resilience enhancement program should be considered. PMID:26539013

The Relation between the Fear-Avoidance Model and Constructs from the Social Cognitive Theory in Acute WAD.

PubMed

Sandborgh, Maria; Johansson, Ann-Christin; Söderlund, Anne

2016-01-01

In the fear-avoidance (FA) model social cognitive constructs could add to explaining the disabling process in whiplash associated disorder (WAD). The aim was to exemplify the possible input from Social Cognitive Theory on the FA model. Specifically the role of functional self-efficacy and perceived responses from a spouse/intimate partner was studied. A cross-sectional and correlational design was used. Data from 64 patients with acute WAD were used. Measures were pain intensity measured with a numerical rating scale, the Pain Disability Index, support, punishing responses, solicitous responses, and distracting responses subscales from the Multidimensional Pain Inventory, the Catastrophizing subscale from the Coping Strategies Questionnaire, the Tampa Scale of Kinesiophobia, and the Self-Efficacy Scale. Bivariate correlational, simple linear regression, and multiple regression analyses were used. In the statistical prediction models high pain intensity indicated high punishing responses, which indicated high catastrophizing. High catastrophizing indicated high fear of movement, which indicated low self-efficacy. Low self-efficacy indicated high disability, which indicated high pain intensity. All independent variables together explained 66.4% of the variance in pain disability, p < 0.001. Results suggest a possible link between one aspect of the social environment, perceived punishing responses from a spouse/intimate partner, pain intensity, and catastrophizing. Further, results support a mediating role of self-efficacy between fear of movement and disability in WAD.

Development and Validation of MMPI-2-RF Scales for Indexing Triarchic Psychopathy Constructs.

PubMed

Sellbom, Martin; Drislane, Laura E; Johnson, Alexandria K; Goodwin, Brandee E; Phillips, Tasha R; Patrick, Christopher J

2016-10-01

The triarchic model characterizes psychopathy in terms of three distinct dispositional constructs of boldness, meanness, and disinhibition. The model can be operationalized through scales designed specifically to index these domains or by using items from other inventories that provide coverage of related constructs. The present study sought to develop and validate scales for assessing the triarchic model domains using items from the Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF). A consensus rating approach was used to identify items relevant to each triarchic domain, and following psychometric refinement, the resulting MMPI-2-RF-based triarchic scales were evaluated for convergent and discriminant validity in relation to multiple psychopathy-relevant criterion variables in offender and nonoffender samples. Expected convergent and discriminant associations were evident very clearly for the Boldness and Disinhibition scales and somewhat less clearly for the Meanness scale. Moreover, hierarchical regression analyses indicated that all MMPI-2-RF triarchic scales incremented standard MMPI-2-RF scale scores in predicting extant triarchic model scale scores. The widespread use of MMPI-2-RF in clinical and forensic settings provides avenues for both clinical and research applications in contexts where traditional psychopathy measures are less likely to be administered. © The Author(s) 2015.

Noninvasive spectral imaging of skin chromophores based on multiple regression analysis aided by Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Nishidate, Izumi; Wiswadarma, Aditya; Hase, Yota; Tanaka, Noriyuki; Maeda, Takaaki; Niizeki, Kyuichi; Aizu, Yoshihisa

2011-08-01

In order to visualize melanin and blood concentrations and oxygen saturation in human skin tissue, a simple imaging technique based on multispectral diffuse reflectance images acquired at six wavelengths (500, 520, 540, 560, 580 and 600nm) was developed. The technique utilizes multiple regression analysis aided by Monte Carlo simulation for diffuse reflectance spectra. Using the absorbance spectrum as a response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as predictor variables, multiple regression analysis provides regression coefficients. Concentrations of melanin and total blood are then determined from the regression coefficients using conversion vectors that are deduced numerically in advance, while oxygen saturation is obtained directly from the regression coefficients. Experiments with a tissue-like agar gel phantom validated the method. In vivo experiments with human skin of the human hand during upper limb occlusion and of the inner forearm exposed to UV irradiation demonstrated the ability of the method to evaluate physiological reactions of human skin tissue.

Psychological factors influence the gastroesophageal reflux disease (GERD) and their effect on quality of life among firefighters in South Korea.

PubMed

Jang, Seung-Ho; Ryu, Han-Seung; Choi, Suck-Chei; Lee, Sang-Yeol

2016-10-01

The purpose of this study was to examine psychosocial factors related to gastroesophageal reflux disease (GERD) and their effects on quality of life (QOL) in firefighters. Data were collected from 1217 firefighters in a Korean province. We measured psychological symptoms using the scale. In order to observe the influence of the high-risk group on occupational stress, we conduct logistic multiple linear regression. The correlation between psychological factors and QOL was also analyzed and performed a hierarchical regression analysis. GERD was observed in 32.2% of subjects. Subjects with GERD showed higher depressive symptom, anxiety and occupational stress scores, and lower self-esteem and QOL scores relative to those observed in GERD - negative subject. GERD risk was higher for the following occupational stress subcategories: job demand, lack of reward, interpersonal conflict, and occupational climate. The stepwise regression analysis showed that depressive symptoms, occupational stress, self-esteem, and anxiety were the best predictors of QOL. The results suggest that psychological and medical approaches should be combined in GERD assessment.

Psychological factors influence the gastroesophageal reflux disease (GERD) and their effect on quality of life among firefighters in South Korea

PubMed Central

Jang, Seung-Ho; Ryu, Han-Seung; Choi, Suck-Chei; Lee, Sang-Yeol

2016-01-01

Objectives The purpose of this study was to examine psychosocial factors related to gastroesophageal reflux disease (GERD) and their effects on quality of life (QOL) in firefighters. Methods Data were collected from 1217 firefighters in a Korean province. We measured psychological symptoms using the scale. In order to observe the influence of the high-risk group on occupational stress, we conduct logistic multiple linear regression. The correlation between psychological factors and QOL was also analyzed and performed a hierarchical regression analysis. Results GERD was observed in 32.2% of subjects. Subjects with GERD showed higher depressive symptom, anxiety and occupational stress scores, and lower self-esteem and QOL scores relative to those observed in GERD – negative subject. GERD risk was higher for the following occupational stress subcategories: job demand, lack of reward, interpersonal conflict, and occupational climate. The stepwise regression analysis showed that depressive symptoms, occupational stress, self-esteem, and anxiety were the best predictors of QOL. Conclusions The results suggest that psychological and medical approaches should be combined in GERD assessment. PMID:27691373

Meta-analysis of prediction model performance across multiple studies: Which scale helps ensure between-study normality for the C-statistic and calibration measures?

PubMed

Snell, Kym Ie; Ensor, Joie; Debray, Thomas Pa; Moons, Karel Gm; Riley, Richard D

2017-01-01

If individual participant data are available from multiple studies or clusters, then a prediction model can be externally validated multiple times. This allows the model's discrimination and calibration performance to be examined across different settings. Random-effects meta-analysis can then be used to quantify overall (average) performance and heterogeneity in performance. This typically assumes a normal distribution of 'true' performance across studies. We conducted a simulation study to examine this normality assumption for various performance measures relating to a logistic regression prediction model. We simulated data across multiple studies with varying degrees of variability in baseline risk or predictor effects and then evaluated the shape of the between-study distribution in the C-statistic, calibration slope, calibration-in-the-large, and E/O statistic, and possible transformations thereof. We found that a normal between-study distribution was usually reasonable for the calibration slope and calibration-in-the-large; however, the distributions of the C-statistic and E/O were often skewed across studies, particularly in settings with large variability in the predictor effects. Normality was vastly improved when using the logit transformation for the C-statistic and the log transformation for E/O, and therefore we recommend these scales to be used for meta-analysis. An illustrated example is given using a random-effects meta-analysis of the performance of QRISK2 across 25 general practices.

Using the Coefficient of Determination "R"[superscript 2] to Test the Significance of Multiple Linear Regression

ERIC Educational Resources Information Center

Quinino, Roberto C.; Reis, Edna A.; Bessegato, Lupercio F.

2013-01-01

This article proposes the use of the coefficient of determination as a statistic for hypothesis testing in multiple linear regression based on distributions acquired by beta sampling. (Contains 3 figures.)

Estimating Interaction Effects With Incomplete Predictor Variables

PubMed Central

Enders, Craig K.; Baraldi, Amanda N.; Cham, Heining

2014-01-01

The existing missing data literature does not provide a clear prescription for estimating interaction effects with missing data, particularly when the interaction involves a pair of continuous variables. In this article, we describe maximum likelihood and multiple imputation procedures for this common analysis problem. We outline 3 latent variable model specifications for interaction analyses with missing data. These models apply procedures from the latent variable interaction literature to analyses with a single indicator per construct (e.g., a regression analysis with scale scores). We also discuss multiple imputation for interaction effects, emphasizing an approach that applies standard imputation procedures to the product of 2 raw score predictors. We thoroughly describe the process of probing interaction effects with maximum likelihood and multiple imputation. For both missing data handling techniques, we outline centering and transformation strategies that researchers can implement in popular software packages, and we use a series of real data analyses to illustrate these methods. Finally, we use computer simulations to evaluate the performance of the proposed techniques. PMID:24707955

Gradients in Depressive Symptoms by Socioeconomic Position Among Men Who Have Sex With Men in the EXPLORE Study.

PubMed

Pakula, Basia; Marshall, Brandon D L; Shoveller, Jean A; Chesney, Margaret A; Coates, Thomas J; Koblin, Beryl; Mayer, Kenneth; Mimiaga, Matthew; Operario, Don

2016-08-01

This study examines gradients in depressive symptoms by socioeconomic position (SEP; i.e., income, education, employment) in a sample of men who have sex with men (MSM). Data were used from EXPLORE, a randomized, controlled behavioral HIV prevention trial for HIV-uninfected MSM in six U.S. cities (n = 4,277). Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression scale (short form). Multiple linear regressions were fitted with interaction terms to assess additive and multiplicative relationships between SEP and depressive symptoms. Depressive symptoms were more prevalent among MSM with lower income, lower educational attainment, and those in the unemployed/other employment category. Income, education, and employment made significant contributions in additive models after adjustment. The employment-income interaction was statistically significant, indicating a multiplicative effect. This study revealed gradients in depressive symptoms across SEP of MSM, pointing to income and employment status and, to a lesser extent, education as key factors for understanding heterogeneity of depressive symptoms.

Personality traits associated with intrinsic academic motivation in medical students.

PubMed

Tanaka, Masaaki; Mizuno, Kei; Fukuda, Sanae; Tajima, Seiki; Watanabe, Yasuyoshi

2009-04-01

Motivation is one of the most important psychological concepts in education and is related to academic outcomes in medical students. In this study, the relationships between personality traits and intrinsic academic motivation were examined in medical students. The study group consisted of 119 Year 2 medical students at Osaka City University Graduate School of Medicine. They completed questionnaires dealing with intrinsic academic motivation (the Intrinsic Motivation Scale toward Learning) and personality (the Temperament and Character Inventory [TCI]). On simple regression analyses, the TCI dimensions of persistence, self-directedness, co-operativeness and self-transcendence were positively associated with intrinsic academic motivation. On multiple regression analysis adjusted for age and gender, the TCI dimensions of persistence, self-directedness and self-transcendence were positively associated with intrinsic academic motivation. The temperament dimension of persistence and the character dimensions of self-directedness and self-transcendence are associated with intrinsic academic motivation in medical students.

Predictors of hopelessness among clinically depressed youth.

PubMed

Becker-Weidman, Emily G; Reinecke, Mark A; Jacobs, Rachel H; Martinovich, Zoran; Silva, Susan G; March, John S

2009-05-01

Factors that distinguish depressed individuals who become hopeless from those who do not are poorly understood. In this study, predictors of hopelessness were examined in a sample of 439 clinically depressed adolescents participating in the Treatment for Adolescents with Depression Study (TADS). The total score of the Beck Hopelessness Scale (BHS) was used to assess hopelessness at baseline. Multiple regression and logistic regression analyses were conducted to evaluate the extent to which variables were associated with hopelessness and determine which cluster of measures best predicted clinically significantly hopelessness. Hopelessness was associated with greater depression severity, poor social problem-solving, cognitive distortions, and family conflict. View of self, view of the world, internal attributional style, need for social approval, positive problem-solving orientation, and family problems consistently emerged as the best predictors of hopelessness in depressed youth. Cognitive and familial factors predict those depressed youth who have high levels of hopelessness.

Simultaneous high-speed schlieren and OH chemiluminescence imaging in a hybrid rocket combustor at elevated pressures

NASA Astrophysics Data System (ADS)

Miller, Victor; Jens, Elizabeth T.; Mechentel, Flora S.; Cantwell, Brian J.; Stanford Propulsion; Space Exploration Group Team

2014-11-01

In this work, we present observations of the overall features and dynamics of flow and combustion in a slab-type hybrid rocket combustor. Tests were conducted in the recently upgraded Stanford Combustion Visualization Facility, a hybrid rocket combustor test platform capable of generating constant mass-flux flows of oxygen. High-speed (3 kHz) schlieren and OH chemiluminescence imaging were used to visualize the flow. We present imaging results for the combustion of two different fuel grains, a classic, low regression rate polymethyl methacrylate (PMMA), and a high regression rate paraffin, and all tests were conducted in gaseous oxygen. Each fuel grain was tested at multiple free-stream pressures at constant oxidizer mass flux (40 kg/m2s). The resulting image sequences suggest that aspects of the dynamics and scaling of the system depend strongly on both pressure and type of fuel.

The Association between Noise, Cortisol and Heart Rate in a Small-Scale Gold Mining Community—A Pilot Study

PubMed Central

Green, Allyson; Jones, Andrew D.; Sun, Kan; Neitzel, Richard L.

2015-01-01

We performed a cross-sectional pilot study on salivary cortisol, heart rate, and personal noise exposures in a small-scale gold mining village in northeastern Ghana in 2013. Cortisol level changes between morning and evening among participants showed a relatively low decline in cortisol through the day (−1.44 ± 4.27 nmol/L, n = 18), a pattern consistent with chronic stress. A multiple linear regression, adjusting for age, sex, smoking status, and time between samples indicated a significant increase of 0.25 nmol/L cortisol from afternoon to evening per 1 dBA increase in equivalent continuous noise exposure (Leq) over that period (95% CI: 0.08–0.42, Adj R2 = 0.502, n = 17). A mixed effect linear regression model adjusting for age and sex indicated a significant increase of 0.29 heart beats per minute (BPM) for every 1 dB increase in Leq. Using standard deviations (SDs) as measures of variation, and adjusting for age and sex over the sampling period, we found that a 1 dBA increase in noise variation over time (Leq SD) was associated with a 0.5 BPM increase in heart rate SD (95% CI: 0.04–−0.9, Adj. R2 = 0.229, n = 16). Noise levels were consistently high, with 24-hour average Leq exposures ranging from 56.9 to 92.0 dBA, with a mean daily Leq of 82.2 ± 7.3 dBA (mean monitoring duration 22.1 ± 1.9 hours, n = 22). Ninety-five percent of participants had 24-hour average Leq noise levels over the 70 dBA World health Organization (WHO) guideline level for prevention of hearing loss. These findings suggest that small-scale mining communities may face multiple, potentially additive health risks that are not yet well documented, including hearing loss and cardiovascular effects of stress and noise. PMID:26308019

The Association between Noise, Cortisol and Heart Rate in a Small-Scale Gold Mining Community-A Pilot Study.

PubMed

Green, Allyson; Jones, Andrew D; Sun, Kan; Neitzel, Richard L

2015-08-21

We performed a cross-sectional pilot study on salivary cortisol, heart rate, and personal noise exposures in a small-scale gold mining village in northeastern Ghana in 2013. Cortisol level changes between morning and evening among participants showed a relatively low decline in cortisol through the day (-1.44 ± 4.27 nmol/L, n = 18), a pattern consistent with chronic stress. A multiple linear regression, adjusting for age, sex, smoking status, and time between samples indicated a significant increase of 0.25 nmol/L cortisol from afternoon to evening per 1 dBA increase in equivalent continuous noise exposure (Leq) over that period (95% CI: 0.08-0.42, Adj R(2) = 0.502, n = 17). A mixed effect linear regression model adjusting for age and sex indicated a significant increase of 0.29 heart beats per minute (BPM) for every 1 dB increase in Leq. Using standard deviations (SDs) as measures of variation, and adjusting for age and sex over the sampling period, we found that a 1 dBA increase in noise variation over time (Leq SD) was associated with a 0.5 BPM increase in heart rate SD (95% CI: 0.04--0.9, Adj. R(2) = 0.229, n = 16). Noise levels were consistently high, with 24-hour average Leq exposures ranging from 56.9 to 92.0 dBA, with a mean daily Leq of 82.2 ± 7.3 dBA (mean monitoring duration 22.1 ± 1.9 hours, n = 22). Ninety-five percent of participants had 24-hour average Leq noise levels over the 70 dBA World health Organization (WHO) guideline level for prevention of hearing loss. These findings suggest that small-scale mining communities may face multiple, potentially additive health risks that are not yet well documented, including hearing loss and cardiovascular effects of stress and noise.

Perceived Maternal Role Competence among the Mothers Attending Immunization Clinics of Dharan, Nepal.

PubMed

Shrooti, Shah; Mangala, Shrestha; Nirmala, Pokharel; Devkumari, Shrestha; Dharanidhar, Baral

2016-04-01

Being a mother is considered by many women as their most important role in life. Women's perceptions of their abilities to manage the demands of parenting and the parenting skills they posses are reflected by perceived maternal role competence. The present study was carried out to assess the perceived maternal role competence and its associated factors among mothers. A descriptive cross-sectional research study was carried out on 290 mothers of infant in four immunization clinics of Dharan, Nepal. Data were collected using a standardized predesigned, pretested questionnaire (Parent sense of competence scale, Rosenberg's self esteem scale, Maternity social support scale). The data were analyzed using descriptive and inferential statistics and multiple regression analysis at 0.05 level of significance. The mean score of the perceived maternal role competence obtained by mothers was 64.34±7.90 and those of knowledge/skill and valuing/comfort subscale were 31±6.01 and 33±3.75, respectively. There was a significant association between perceived maternal role competence and factors as the age of the mother (P<0.001), educational status (P=0.015), occupation (P=0.001) and readiness for pregnancy (P=0.022). The study findings revealed a positive correlation between perceived maternal role competence and age at marriage (r=0.132, P=0.024), per capita income (r=0.118, P=0.045), self esteem (r=0.379, P<0.001), social support (r=0.272, P<0.001), and number of support persons (r=0.119, P=0.043). The results of the step wise multiple regression analysis revealed that the major predictor of perceived maternal role competence was self esteem. The factors associated with perceived maternal role competence were age, education, occupation, per capita income, self esteem, social support, and the number of support persons.

Impact of Land Use on PM2.5 Pollution in a Representative City of Middle China.

PubMed

Yang, Haiou; Chen, Wenbo; Liang, Zhaofeng

2017-04-26

Fine particulate matter (PM 2.5 ) pollution has become one of the greatest urban issues in China. Studies have shown that PM 2.5 pollution is strongly related to the land use pattern at the micro-scale and optimizing the land use pattern has been suggested as an approach to mitigate PM 2.5 pollution. However, there are only a few researches analyzing the effect of land use on PM 2.5 pollution. This paper employed land use regression (LUR) models and statistical analysis to explore the effect of land use on PM 2.5 pollution in urban areas. Nanchang city, China, was taken as the study area. The LUR models were used to simulate the spatial variations of PM 2.5 concentrations. Analysis of variance and multiple comparisons were employed to study the PM 2.5 concentration variances among five different types of urban functional zones. Multiple linear regression was applied to explore the PM 2.5 concentration variances among the same type of urban functional zone. The results indicate that the dominant factor affecting PM 2.5 pollution in the Nanchang urban area was the traffic conditions. Significant variances of PM 2.5 concentrations among different urban functional zones throughout the year suggest that land use types generated a significant impact on PM 2.5 concentrations and the impact did not change as the seasons changed. Land use intensity indexes including the building volume rate, building density, and green coverage rate presented an insignificant or counter-intuitive impact on PM 2.5 concentrations when studied at the spatial scale of urban functional zones. Our study demonstrates that land use can greatly affect the PM 2.5 levels. Additionally, the urban functional zone was an appropriate spatial scale to investigate the impact of land use type on PM 2.5 pollution in urban areas.

Impact of Land Use on PM2.5 Pollution in a Representative City of Middle China

PubMed Central

Yang, Haiou; Chen, Wenbo; Liang, Zhaofeng

2017-01-01

Fine particulate matter (PM2.5) pollution has become one of the greatest urban issues in China. Studies have shown that PM2.5 pollution is strongly related to the land use pattern at the micro-scale and optimizing the land use pattern has been suggested as an approach to mitigate PM2.5 pollution. However, there are only a few researches analyzing the effect of land use on PM2.5 pollution. This paper employed land use regression (LUR) models and statistical analysis to explore the effect of land use on PM2.5 pollution in urban areas. Nanchang city, China, was taken as the study area. The LUR models were used to simulate the spatial variations of PM2.5 concentrations. Analysis of variance and multiple comparisons were employed to study the PM2.5 concentration variances among five different types of urban functional zones. Multiple linear regression was applied to explore the PM2.5 concentration variances among the same type of urban functional zone. The results indicate that the dominant factor affecting PM2.5 pollution in the Nanchang urban area was the traffic conditions. Significant variances of PM2.5 concentrations among different urban functional zones throughout the year suggest that land use types generated a significant impact on PM2.5 concentrations and the impact did not change as the seasons changed. Land use intensity indexes including the building volume rate, building density, and green coverage rate presented an insignificant or counter-intuitive impact on PM2.5 concentrations when studied at the spatial scale of urban functional zones. Our study demonstrates that land use can greatly affect the PM2.5 levels. Additionally, the urban functional zone was an appropriate spatial scale to investigate the impact of land use type on PM2.5 pollution in urban areas. PMID:28445430

Impact of sleep quality on the quality of life of patients with Parkinson's disease: a questionnaire based study.

PubMed

Pandey, Shweta; Bajaj, Bhupender Kumar; Wadhwa, Ankur; Anand, Kuljeet Singh

2016-09-01

Poor sleep quality contributes to the inferior quality of life of patients with Parkinson's disease (PD) despite appropriate treatment of motor symptoms. The literature about the impact of sleep quality on quality of life of patients with PD is as yet sparse. One hundred patients of PD diagnosed as per UK Brain Bank criteria were assessed for severity and stage of PD using UPDRS and modified Hoehn &Yahr scales. The quality of sleep was assessed by Pittsburgh Sleep Quality Index and excessive daytime somnolence (EDS) was evaluated using Epworth Sleepiness Scale. Parkinson's Disease Questionnaire -39 (PDQ-39) was used to determine quality of life of the patients. Comorbid depression and anxiety were assessed using Inventory of Depressive Symptoms-Self Rated and Hamilton Anxiety Rating Scale. Pearson's correlation and multiple linear regressions were used to analyze relation of sleep quality with quality of life of patients. Fifty patients had poor sleep quality. EDS was present in only 9 patients. Co-morbid depression and anxiety were present in 52 and 34 patients respectively. While the motor severity assessed by UPDRS-III was observed to adversely affect quality of life, it did not negatively impact quality of sleep. Higher score on UPDRS-total and UPDRS IV suggesting advanced disease correlated with poor sleep quality. Depression and anxiety were significantly more frequent in patients with poor sleep quality (p<0.01). Patients with poor sleep quality had worse quality of life (r=0.338, p<0.05). Depression and anxiety were also observed to have significant negative impact on quality of life of PD patients (p<0.01). Poor sleep quality was not found to be an independent predictor of quality of life using multiple linear regression analysis. Poor sleep quality along with comorbid depression, anxiety and advanced stage of disease is associated with poor quality of life. Copyright © 2016 Elsevier B.V. All rights reserved.

Relationship between the non-motor items of the MDS-UPDRS and Quality of Life in patients with Parkinson's disease.

PubMed

Skorvanek, Matej; Rosenberger, Jaroslav; Minar, Michal; Grofik, Milan; Han, Vladimir; Groothoff, Johan W; Valkovic, Peter; Gdovinova, Zuzana; van Dijk, Jitse P

2015-01-01

The Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) is a newly developed comprehensive tool to assess Parkinson's disease (PD), which covers a wider range of non-motor PD manifestations than the original UPDRS scale. The aim of this study was to assess the relationship between the MDS-UPDRS and Quality of Life (QoL) and to analyze the relationship between individual MDS-UPDRS non-motor items and QoL. A total of 291 PD patients were examined in a multicenter Slovak study. Patients were assessed by the MDS-UPDRS, HY scale and PDQ39. Data were analyzed using the multiple regression analyses. The mean participant age was 68.0 ± 9.0 years, 53.5% were men, mean disease duration was 8.3 ± 5.3 years and mean HY was 2.7 ± 1.0. In a multiple regression analysis model the PDQ39 summary index was related to MDS-UPDRS parts II, I and IV respectively, but not to part III. Individual MDS-UPDRS non-motor items related to the PDQ39 summary index in the summary group and in the non-fluctuating patients subgroup were pain, fatigue and features of dopamine dysregulation syndrome (DDS). In the fluctuating PD patient subgroup, PDQ39 was related to pain and Depressed mood items. Other MDS-UPDRS non-motor items e.g. Anxious mood, Apathy, Cognitive impairment, Hallucinations and psychosis, Sleep problems, Daytime sleepiness and Urinary problems were related to some PDQ39 domains. The overall burden of NMS in PD is more important in terms of QoL than motor symptoms. Individual MDS-UPDRS non-motor items related to worse QoL are especially pain and other sensations, fatigue and features of DDS. Copyright © 2015 Elsevier B.V. All rights reserved.

A new instrument to measure quality of life of heart failure family caregivers.

PubMed

Nauser, Julie A; Bakas, Tamilyn; Welch, Janet L

2011-01-01

Family caregivers of heart failure (HF) patients experience poor physical and mental health leading to poor quality of life. Although several quality-of-life measures exist, they are often too generic to capture the unique experience of this population. The purpose of this study was to evaluate the psychometric properties of the Family Caregiver Quality of Life (FAMQOL) Scale that was designed to assess the physical, psychological, social, and spiritual dimensions of quality of life among caregivers of HF patients. Psychometric testing of the FAMQOL with 100 HF family caregivers was conducted using item analysis, Cronbach α, intraclass correlation, factor analysis, and hierarchical multiple regression guided by a conceptual model. Caregivers were predominately female (89%), white, (73%), and spouses (62%). Evidence of internal consistency reliability (α=.89) was provided for the FAMQOL, with item-total correlations of 0.39 to 0.74. Two-week test-retest reliability was supported by an intraclass correlation coefficient of 0.91. Using a 1-factor solution and principal axis factoring, loadings ranged from 0.31 to 0.78, with 41% of the variance explained by the first factor (eigenvalue=6.5). With hierarchical multiple regression, 56% of the FAMQOL variance was explained by model constructs (F8,91=16.56, P<.001). Criterion-related validity was supported by correlations with SF-36 General (r=0.45, P<.001) and Mental (r=0.59, P<.001) Health subscales and Bakas Caregiving Outcomes Scale (r=0.73, P<.001). Evidence of internal and test-retest reliability and construct and criterion validity was provided for physical, psychological, and social well-being subscales. The 16-item FAMQOL is a brief, easy-to-administer instrument that has evidence of reliability and validity in HF family caregivers. Physical, psychological, and social well-being can be measured with 4-item subscales. The FAMQOL scale could serve as a valuable measure in research, as well as an assessment tool to identify caregivers in need of intervention.

Attitudes toward concordance and self-efficacy in decision making: a cross-sectional study on pharmacist-patient consultations.

PubMed

Ng, Yew Keong; Shah, Noraida Mohamed; Loong, Ly Sia; Pee, Lay Ting; Hidzir, Sarina Anim M; Chong, Wei Wen

2018-01-01

This study investigated patients' and pharmacists' attitudes toward concordance in a pharmacist-patient consultation and how patients' attitudes toward concordance relate to their involvement and self-efficacy in decision making associated with medication use. A cross-sectional study was conducted among patients with chronic diseases and pharmacists from three public hospitals in Malaysia. The Revised United States Leeds Attitudes toward Concordance (RUS-LATCon) was used to measure attitudes toward concordance in both patients and pharmacists. Patients also rated their perceived level of involvement in decision making and completed the Decision Self-Efficacy scale. One-way analysis of variance (ANOVA) and independent t -test were used to determine significant differences between different subgroups on attitudes toward concordance, and multiple linear regression was performed to find the predictors of patients' self-efficacy in decision making. A total of 389 patients and 93 pharmacists participated in the study. Pharmacists and patients scored M=3.92 (SD=0.37) and M=3.84 (SD=0.46) on the RUS-LATCon scale, respectively. Seven items were found to be significantly different between pharmacists and patients on the subscale level. Patients who felt fully involved in decision making (M=3.94, SD=0.462) scored significantly higher on attitudes toward concordance than those who felt partially involved (M=3.82, SD=0.478) and not involved at all (M=3.68, SD=0.471; p <0.001). Patients had an average score of 76.7% (SD=14.73%) on the Decision Self-Efficacy scale. In multiple linear regression analysis, ethnicity, number of medications taken by patients, patients' perceived level of involvement, and attitudes toward concordance are significant predictors of patients' self-efficacy in decision making ( p <0.05). Patients who felt involved in their consultations had more positive attitudes toward concordance and higher confidence in making an informed decision. Further study is recommended on interventions involving pharmacists in supporting patients' involvement in medication-related decision making.

Identifying maternal and infant factors associated with newborn size in rural Bangladesh by partial least squares (PLS) regression analysis

PubMed Central

Rahman, Md. Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D. W.; Labrique, Alain B.; Rashid, Mahbubur; Christian, Parul; West, Keith P.

2017-01-01

Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 − -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset. PMID:29261760

Identifying maternal and infant factors associated with newborn size in rural Bangladesh by partial least squares (PLS) regression analysis.

PubMed

Kabir, Alamgir; Rahman, Md Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D W; Labrique, Alain B; Rashid, Mahbubur; Christian, Parul; West, Keith P

2017-01-01

Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 - -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset.

Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings.

PubMed

Choi, Jae-Seok; Kim, Munchurl

2017-03-01

Super-resolution (SR) has become more vital, because of its capability to generate high-quality ultra-high definition (UHD) high-resolution (HR) images from low-resolution (LR) input images. Conventional SR methods entail high computational complexity, which makes them difficult to be implemented for up-scaling of full-high-definition input images into UHD-resolution images. Nevertheless, our previous super-interpolation (SI) method showed a good compromise between Peak-Signal-to-Noise Ratio (PSNR) performances and computational complexity. However, since SI only utilizes simple linear mappings, it may fail to precisely reconstruct HR patches with complex texture. In this paper, we present a novel SR method, which inherits the large-to-small patch conversion scheme from SI but uses global regression based on local linear mappings (GLM). Thus, our new SR method is called GLM-SI. In GLM-SI, each LR input patch is divided into 25 overlapped subpatches. Next, based on the local properties of these subpatches, 25 different local linear mappings are applied to the current LR input patch to generate 25 HR patch candidates, which are then regressed into one final HR patch using a global regressor. The local linear mappings are learned cluster-wise in our off-line training phase. The main contribution of this paper is as follows: Previously, linear-mapping-based conventional SR methods, including SI only used one simple yet coarse linear mapping to each patch to reconstruct its HR version. On the contrary, for each LR input patch, our GLM-SI is the first to apply a combination of multiple local linear mappings, where each local linear mapping is found according to local properties of the current LR patch. Therefore, it can better approximate nonlinear LR-to-HR mappings for HR patches with complex texture. Experiment results show that the proposed GLM-SI method outperforms most of the state-of-the-art methods, and shows comparable PSNR performance with much lower computational complexity when compared with a super-resolution method based on convolutional neural nets (SRCNN15). Compared with the previous SI method that is limited with a scale factor of 2, GLM-SI shows superior performance with average 0.79 dB higher in PSNR, and can be used for scale factors of 3 or higher.

Predicting vulnerability to hopelessness. A longitudinal analysis.

PubMed

Bonner, R L; Rich, A R

1991-01-01

The role of loneliness, irrational beliefs, and deficient reasons for living in predicting vulnerability to hopelessness under conditions of negative life stress was examined. Subjects (N = 178) completed the UCLA Loneliness Scale. Rational Beliefs Inventory, and the Reasons for Living Inventory at the beginning of the semester. Then, at midterm, measures of negative life stress, depression, and hopelessness were obtained from the same subjects. It was hypothesized that the vulnerability factors would interact with negative life stress to predict hopelessness, independent of depressed mood. The results of multiple regression analyses supported this hypothesis. Implications for research, prevention, and treatment are noted.

Relationships between locus of control and paranormal beliefs.

PubMed

Newby, Robert W; Davis, Jessica Boyette

2004-06-01

The present study investigated the associations between scores on paranormal beliefs, locus of control, and certain psychological processes such as affect and cognitions as measured by the Linguistic Inquiry and Word Count. Analysis yielded significant correlations between scores on Locus of Control and two subscales of Tobacyk's (1988) Revised Paranormal Beliefs Scale, New Age Philosophy and Traditional Paranormal Beliefs. A step-wise multiple regression analysis indicated that Locus of Control was significantly related to New Age Philosophy. Other correlations were found between Tobacyk's subscales, Locus of Control, and three processes measured by the Linguistic Inquiry and Word Count.

Neurocognition and community outcome in schizophrenia: long-term predictive validity.

PubMed

Fujii, Daryl E; Wylie, A Michael

2003-02-01

The present study examined the predictive validity of neuropsychological measures to functional outcome in 26 schizophrenic patients 15-plus year post-testing. Outcome measures included score on the Resource Associated Functional Level Scale (RAFLS), number of state hospital admissions, and total duration of state hospital inpatient stay. Results of several stepwise multiple regressions revealed that verbal memory significantly predicted RAFLS score, accounting for nearly half of the variance. Trails B significantly predicted duration of state hospital inpatient status. Discussion focused on the utility of these measures for clinicians and system planners. Copyright 2002 Elsevier Science B.V.

The M Word: Multicollinearity in Multiple Regression.

ERIC Educational Resources Information Center

Morrow-Howell, Nancy

1994-01-01

Notes that existence of substantial correlation between two or more independent variables creates problems of multicollinearity in multiple regression. Discusses multicollinearity problem in social work research in which independent variables are usually intercorrelated. Clarifies problems created by multicollinearity, explains detection of…

[Prediction model of health workforce and beds in county hospitals of Hunan by multiple linear regression].

PubMed

Ling, Ru; Liu, Jiawang

2011-12-01

To construct prediction model for health workforce and hospital beds in county hospitals of Hunan by multiple linear regression. We surveyed 16 counties in Hunan with stratified random sampling according to uniform questionnaires,and multiple linear regression analysis with 20 quotas selected by literature view was done. Independent variables in the multiple linear regression model on medical personnels in county hospitals included the counties' urban residents' income, crude death rate, medical beds, business occupancy, professional equipment value, the number of devices valued above 10 000 yuan, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, and utilization rate of hospital beds. Independent variables in the multiple linear regression model on county hospital beds included the the population of aged 65 and above in the counties, disposable income of urban residents, medical personnel of medical institutions in county area, business occupancy, the total value of professional equipment, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, utilization rate of hospital beds, and length of hospitalization. The prediction model shows good explanatory and fitting, and may be used for short- and mid-term forecasting.

Need for cognition and cognitive performance from a cross-cultural perspective: examples of academic success and solving anagrams.

PubMed

Gülgöz, S

2001-01-01

The cross-cultural validity of the Need for Cognition Scale and its relationship with cognitive performance were investigated in two studies. In the first study, the relationships between the scale and university entrance scores, course grades, study skills, and social desirability were examined. Using the short form of the Turkish version of the Need for Cognition Scale (S. Gülöz & C. J. Sadowski, 1995) no correlation with academic performance was found but there was significant correlation with a study skills scale and a social desirability scale created for this study. When regression analysis was used to predict grade point average, the Need for Cognition Scale was a significant predictor. In the second study, participants low or high in need for cognition solved multiple-solution anagrams. The instructions preceding the task set the participants' expectations regarding task difficulty. An interaction between expectation and need for cognition indicated that participants with low need for cognition performed worse when they expected difficult problems. Results of the two studies showed that need for cognition has cross-cultural validity and that its effect on cognitive performance was mediated by other variables.

Insight and neurocognitive functioning in bipolar subjects.

PubMed

Shad, Mujeeb U; Prasad, Konasale; Forman, Steven D; Haas, Gretchen L; Walker, Jon D; Pisarov, Liubomir A; Goldstein, Gerald

2015-01-01

Insight concerning having a mental illness has been found to influence outcome and effectiveness of treatment. It has been studied mainly in the area of schizophrenia with few studies addressing other disorders. This study evaluates insight in individuals with bipolar disorder using the Scale to Assess Unawareness of Mental Disorder (SUMD), a comprehensive interview for evaluation of awareness of illness and attribution of symptoms. The hypothesis was that in bipolar disorder level of awareness may be associated with numerous factors including neurocognitive function, structural changes in the frontal lobes and hippocampus evaluated by MRI, neurocognitive status, severity of mania and other psychiatric symptoms and comorbid alcoholism. In order to evaluate this hypothesis 33 individuals with DSM-IV diagnosed bipolar disorder, some with and some without comorbid alcoholism, were administered the SUMD and a number of other procedures including a quantitative MRI measuring volume of the frontal lobes and hippocampus, a brief battery of neurocognitive tests, the Brief Psychiatric Rating Scale, and the Young Mania Rating Scale. The data were analyzed by comparing participants with and without alcoholism on these procedures using t tests and by linear multiple regression, with SUMD ratings of awareness and attribution as the dependent variables and variable sets from the other procedures administered as multivariate independent variables. The median score obtained from the SUMD for current awareness was in a range between full awareness and uncertainty concerning presence of a mental disorder. For attribution, the median score indicated that attribution was usually made to the illness itself. None of the differences between participants with and without comorbid alcoholism were significant for the SUMD awareness and attribution scores, neurocognitive or MRI variables. The multiple regression analyses only showed a significant degree of association between the SUMD awareness score and the Young Mania Rating Scale (r(2)=.632, p<.05). A stepwise analysis indicated that items assessing degree of insight, irritability, and sleep disturbance met criteria for entry into the regression equation. None of the regression analyses for the SUMD attribution item were significant. Apparently unlike the case for schizophrenia, most of the participants, all of whom had bipolar disorder, were aware of their symptoms and correctly related them to a mental disorder. Hypotheses concerning the relationships between degree of unawareness and possible contributors to its development including comorbid alcoholism, cognitive dysfunction and structural reduction of gray matter in the frontal region and hippocampus, were not associated with degree of unawareness but symptoms of mania were significantly associated. The apparent reason for this result is that the sample obtained a SUMD modal awareness score of 1 or 2, reflecting the area between full awareness and uncertainty about having a mental disorder. None of the participants were rated as having a 5 response reflecting the belief that s/he does not have a mental disorder. Published by Elsevier Inc.

The relationship between depressive symptoms among female workers and job stress and sleep quality

PubMed Central

2013-01-01

Objective Recently, workers' mental health has become important focus in the field of occupational health management. Depression is a psychiatric illness with a high prevalence. The association between job stress and depressive symptoms has been demonstrated in many studies. Recently, studies about the association between sleep quality and depressive symptoms have been reported, but there has been no large-scaled study in Korean female workers. Therefore, this study was designed to investigate the relationship between job stress and sleep quality, and depressive symptoms in female workers. Methods From Mar 2011 to Aug 2011, 4,833 female workers in the manufacturing, finance, and service fields at 16 workplaces in Yeungnam province participated in this study, conducted in combination with a worksite-based health checkup initiated by the National Health Insurance Service (NHIS). In this study, a questionnaire survey was carried out using the Korean Occupational Stress Scale-Short Form(KOSS-SF), Pittsburgh Sleep Quality Index(PSQI) and Center for Epidemiological Studies-Depression Scale(CES-D). The collected data was entered in the system and analyzed using the PASW (version 18.0) program. A correlation analysis, cross analysis, multivariate logistic regression analysis, and hierarchical multiple regression analysis were conducted. Results Among the 4,883 subjects, 978 subjects (20.0%) were in the depression group. Job stress(OR=3.58, 95% CI=3.06-4.21) and sleep quality(OR=3.81, 95% CI=3.18-4.56) were strongly associated with depressive symptoms. Hierarchical multiple regression analysis revealed that job stress displayed explanatory powers of 15.6% on depression while sleep quality displayed explanatory powers of 16.2%, showing that job stress and sleep quality had a closer relationship with depressive symptoms, compared to the other factors. The multivariate logistic regression analysis yielded odds ratios between the 7 subscales of job stress and depressive symptoms in the range of 1.30-2.72 and the odds ratio for the lack of reward was the highest(OR=2.72, 95% CI=2.32-3.19). In the partial correlation analysis between each of the 7 subscales of sleep quality (PSQI) and depressive symptoms, the correlation coefficient of subjective sleep quality and daytime dysfunction were 0.352 and 0.362, respectively. Conclusion This study showed that the depressive symptoms of female workers are closely related to their job stress and sleep quality. In particular, the lack of reward and subjective sleep factors are the greatest contributors to depression. In the future, a large-scale study should be performed to augment the current study and to reflect all age groups in a balanced manner. The findings on job stress, sleep, and depression can be utilized as source data to establish standards for mental health management of the ever increasing numbers of female members of the workplace. PMID:24472381

Quantifying suspended sediment flux in a mixed-land-use urbanizing watershed using a nested-scale study design.

PubMed

Zeiger, Sean; Hubbart, Jason A

2016-01-15

Suspended sediment (SS) remains the most pervasive water quality problem globally and yet, despite progress, SS process understanding remains relatively poor in watersheds with mixed-land-use practices. The main objective of the current work was to investigate relationships between suspended sediment and land use types at multiple spatial scales (n=5) using four years of suspended sediment data collected in a representative urbanized mixed-land-use (forest, agriculture, urban) watershed. Water samples were analyzed for SS using a nested-scale experimental watershed study design (n=836 samples×5 gauging sites). Kruskal-Wallis and Dunn's post-hoc multiple comparison tests were used to test for significant differences (CI=95%, p<0.05) in SS levels between gauging sites. Climate extremes (high precipitation/drought) were observed during the study period. Annual maximum SS concentrations exceeded 2387.6 mg/L. Median SS concentrations decreased by 60% from the agricultural headwaters to the rural/urban interface, and increased by 98% as urban land use increased. Multiple linear regression analysis results showed significant relationships between SS, annual total precipitation (positive correlate), forested land use (negative correlate), agricultural land use (negative correlate), and urban land use (negative correlate). Estimated annual SS yields ranged from 16.1 to 313.0 t km(-2) year(-1) mainly due to differences in annual total precipitation. Results highlight the need for additional studies, and point to the need for improved best management practices designed to reduce anthropogenic SS loading in mixed-land-use watersheds. Copyright © 2015 Elsevier B.V. All rights reserved.

Clinical Correlations of Brain Lesion Location in Multiple Sclerosis: Voxel-Based Analysis of a Large Clinical Trial Dataset.

PubMed

Altermatt, Anna; Gaetano, Laura; Magon, Stefano; Häring, Dieter A; Tomic, Davorka; Wuerfel, Jens; Radue, Ernst-Wilhelm; Kappos, Ludwig; Sprenger, Till

2018-05-29

There is a limited correlation between white matter (WM) lesion load as determined by magnetic resonance imaging and disability in multiple sclerosis (MS). The reasons for this so-called clinico-radiological paradox are diverse and may, at least partly, relate to the fact that not just the overall lesion burden, but also the exact anatomical location of lesions predict the severity and type of disability. We aimed at studying the relationship between lesion distribution and disability using a voxel-based lesion probability mapping approach in a very large dataset of MS patients. T2-weighted lesion masks of 2348 relapsing-remitting MS patients were spatially normalized to standard stereotaxic space by non-linear registration. Relations between supratentorial WM lesion locations and disability measures were assessed using a non-parametric ANCOVA (Expanded Disability Status Scale [EDSS]; Multiple Sclerosis Functional Composite, and subscores; Modified Fatigue Impact Scale) or multinomial ordinal logistic regression (EDSS functional subscores). Data from 1907 (81%) patients were included in the analysis because of successful registration. The lesion mapping showed similar areas to be associated with the different disability scales: periventricular regions in temporal, frontal, and limbic lobes were predictive, mainly affecting the posterior thalamic radiation, the anterior, posterior, and superior parts of the corona radiata. In summary, significant associations between lesion location and clinical scores were found in periventricular areas. Such lesion clusters appear to be associated with impairment of different physical and cognitive abilities, probably because they affect commissural and long projection fibers, which are relevant WM pathways supporting many different brain functions.

The Relationships between Workaholism and Symptoms of Psychiatric Disorders: A Large-Scale Cross-Sectional Study

PubMed Central

Griffiths, Mark D.; Sinha, Rajita; Hetland, Jørn

2016-01-01

Despite the many number of studies examining workaholism, large-scale studies have been lacking. The present study utilized an open web-based cross-sectional survey assessing symptoms of psychiatric disorders and workaholism among 16,426 workers (Mage = 37.3 years, SD = 11.4, range = 16–75 years). Participants were administered the Adult ADHD Self-Report Scale, the Obsession-Compulsive Inventory-Revised, the Hospital Anxiety and Depression Scale, and the Bergen Work Addiction Scale, along with additional questions examining demographic and work-related variables. Correlations between workaholism and all psychiatric disorder symptoms were positive and significant. Workaholism comprised the dependent variable in a three-step linear multiple hierarchical regression analysis. Basic demographics (age, gender, relationship status, and education) explained 1.2% of the variance in workaholism, whereas work demographics (work status, position, sector, and annual income) explained an additional 5.4% of the variance. Age (inversely) and managerial positions (positively) were of most importance. The psychiatric symptoms (ADHD, OCD, anxiety, and depression) explained 17.0% of the variance. ADHD and anxiety contributed considerably. The prevalence rate of workaholism status was 7.8% of the present sample. In an adjusted logistic regression analysis, all psychiatric symptoms were positively associated with being a workaholic. The independent variables explained between 6.1% and 14.4% in total of the variance in workaholism cases. Although most effect sizes were relatively small, the study’s findings expand our understanding of possible psychiatric predictors of workaholism, and particularly shed new insight into the reality of adult ADHD in work life. The study’s implications, strengths, and shortcomings are also discussed. PMID:27192149

Potentially Modifiable Factors Associated With Physical Activity in Individuals With Multiple Sclerosis.

PubMed

Reider, Nadia; Salter, Amber R; Cutter, Gary R; Tyry, Tuula; Marrie, Ruth Ann

2017-04-01

Physical activity levels among persons with multiple sclerosis (MS) are worryingly low. We aimed to identify the factors associated with physical activity for people with MS, with an emphasis on factors that have not been studied previously (bladder and hand dysfunction) and are potentially modifiable. This study was a secondary analysis of data collected in the spring of 2012 during the North American Research Committee on Multiple Sclerosis (NARCOMS) Registry. NARCOMS participants were surveyed regarding smoking using questions from the Behavioral Risk Factor Surveillance Survey; disability using the Patient Determined Disease Steps; fatigue, cognition, spasticity, sensory, bladder, vision and hand function using self-reported Performance Scales; health literacy using the Medical Term Recognition Test; and physical activity using questions from the Health Information National Trends Survey. We used a forward binary logistic regression to develop a predictive model in which physical activity was the outcome variable. Of 8,755 respondents, 1,707 (19.5%) were classified as active and 7,068 (80.5%) as inactive. In logistic regression, being a current smoker, moderate or severe level of disability, depression, fatigue, hand, or bladder dysfunction and minimal to mild spasticity were associated with lower odds of meeting physical activity guidelines. MS type was not linked to activity level. Several modifiable clinical and lifestyle factors influenced physical activity in MS. Prospective studies are needed to evaluate whether modification of these factors can increase physical activity participation in persons with MS. © 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Geographic scale matters in detecting the relationship between neighbourhood food environments and obesity risk: an analysis of driver license records in Salt Lake County, Utah.

PubMed

Fan, Jessie X; Hanson, Heidi A; Zick, Cathleen D; Brown, Barbara B; Kowaleski-Jones, Lori; Smith, Ken R

2014-08-19

Empirical studies of the association between neighbourhood food environments and individual obesity risk have found mixed results. One possible cause of these mixed findings is the variation in neighbourhood geographic scale used. The purpose of this paper was to examine how various neighbourhood geographic scales affected the estimated relationship between food environments and obesity risk. Cross-sectional secondary data analysis. Salt Lake County, Utah, USA. 403,305 Salt Lake County adults 25-64 in the Utah driver license database between 1995 and 2008. Utah driver license data were geo-linked to 2000 US Census data and Dun & Bradstreet business data. Food outlets were classified into the categories of large grocery stores, convenience stores, limited-service restaurants and full-service restaurants, and measured at four neighbourhood geographic scales: Census block group, Census tract, ZIP code and a 1 km buffer around the resident's house. These measures were regressed on individual obesity status using multilevel random intercept regressions. Obesity. Food environment was important for obesity but the scale of the relevant neighbourhood differs for different type of outlets: large grocery stores were not significant at all four geographic scales, limited-service restaurants at the medium-to-large scale (Census tract or larger) and convenience stores and full-service restaurants at the smallest scale (Census tract or smaller). The choice of neighbourhood geographic scale can affect the estimated significance of the association between neighbourhood food environments and individual obesity risk. However, variations in geographic scale alone do not explain the mixed findings in the literature. If researchers are constrained to use one geographic scale with multiple categories of food outlets, using Census tract or 1 km buffer as the neighbourhood geographic unit is likely to allow researchers to detect most significant relationships. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Perceived discrimination, social support, and perceived stress among people living with HIV/AIDS in China.

PubMed

Su, Xiaoyou; Lau, Joseph T F; Mak, Winnie W S; Chen, Lin; Choi, K C; Song, Junmin; Zhang, Yan; Zhao, Guanglu; Feng, Tiejian; Chen, Xi; Liu, Chuliang; Liu, Jun; Liu, De; Cheng, Jinquan

2013-01-01

Perceived stress among people living with HIV/AIDS (PLWH) was associated with severe mental health problems and risk behaviors. Discrimination toward PLWH in China is prevalent. Both perceived discrimination and social supports are determinants of the stress level among PLWH. Psychological support services for PLWH in China are scarce. It is unknown whether social support is a buffer between the perceived discrimination and perceived stress. With written consent, this study surveyed 258 PLWH recruited from multiple sources in two cities in China. Instruments were validated in previous or the present study, including the perceived stress scale for PLWH (PSSHIV), the perceived social support scale (PSSS), and the perceived discrimination scale for PLWH (PDSHIV). Pearson correlations and multiple regression models were fit. PDSHIV was associated with the Overall Scale and all subscales of PSSHIV, whilst lower socioeconomic status in general and lower scores of PSSS were associated with various subscales of PSSHIV. The interaction item (PSSS×PSDHIV) was nonsignificant in modeling PSSHIV, hence no significant moderating effect was detected. Whilst perceived discrimination is a major source of stress and social support can reduce stress among PLWH in China, improved social support cannot buffer the stressful consequences due to perceived discrimination. The results highlight the importance to reduce discrimination toward PLWH and the difficulty to alleviate its negative consequences. It is warranted to improve mental health among PLWH in China and it is still important to foster social support among PLWH as it has direct effects on perceived stress.

Understanding the Patterns and Drivers of Air Pollution on Multiple Time Scales: The Case of Northern China.

PubMed

Liu, Yupeng; Wu, Jianguo; Yu, Deyong; Hao, Ruifang

2018-06-01

China's rapid economic growth during the past three decades has resulted in a number of environmental problems, including the deterioration of air quality. It is necessary to better understand how the spatial pattern of air pollutants varies with time scales and what drive these changes. To address these questions, this study focused on one of the most heavily air-polluted areas in North China. We first quantified the spatial pattern of air pollution, and then systematically examined the relationships of air pollution to several socioeconomic and climatic factors using the constraint line method, correlation analysis, and stepwise regression on decadal, annual, and seasonal scales. Our results indicate that PM 2.5 was the dominant air pollutant in the Beijing-Tianjin-Hebei region, while PM 2.5 and PM 10 were both important pollutants in the Agro-pastoral Transitional Zone (APTZ) region. Our statistical analyses suggest that energy consumption and gross domestic product (GDP) in the industry were the most important factors for air pollution on the decadal scale, but the impacts of climatic factors could also be significant. On the annual and seasonal scales, high wind speed, low relative humidity, and long sunshine duration constrained PM 2.5 accumulation; low wind speed and high relative humidity constrained PM 10 accumulation; and short sunshine duration and high wind speed constrained O 3 accumulation. Our study showed that analyses on multiple temporal scales are not only necessary to determine key drivers of air pollution, but also insightful for understanding the spatial patterns of air pollution, which was important for urban planning and air pollution control.

Understanding the Patterns and Drivers of Air Pollution on Multiple Time Scales: The Case of Northern China

NASA Astrophysics Data System (ADS)

Liu, Yupeng; Wu, Jianguo; Yu, Deyong; Hao, Ruifang

2018-06-01

China's rapid economic growth during the past three decades has resulted in a number of environmental problems, including the deterioration of air quality. It is necessary to better understand how the spatial pattern of air pollutants varies with time scales and what drive these changes. To address these questions, this study focused on one of the most heavily air-polluted areas in North China. We first quantified the spatial pattern of air pollution, and then systematically examined the relationships of air pollution to several socioeconomic and climatic factors using the constraint line method, correlation analysis, and stepwise regression on decadal, annual, and seasonal scales. Our results indicate that PM2.5 was the dominant air pollutant in the Beijing-Tianjin-Hebei region, while PM2.5 and PM10 were both important pollutants in the Agro-pastoral Transitional Zone (APTZ) region. Our statistical analyses suggest that energy consumption and gross domestic product (GDP) in the industry were the most important factors for air pollution on the decadal scale, but the impacts of climatic factors could also be significant. On the annual and seasonal scales, high wind speed, low relative humidity, and long sunshine duration constrained PM2.5 accumulation; low wind speed and high relative humidity constrained PM10 accumulation; and short sunshine duration and high wind speed constrained O3 accumulation. Our study showed that analyses on multiple temporal scales are not only necessary to determine key drivers of air pollution, but also insightful for understanding the spatial patterns of air pollution, which was important for urban planning and air pollution control.

The use of regression analysis in determining reference intervals for low hematocrit and thrombocyte count in multiple electrode aggregometry and platelet function analyzer 100 testing of platelet function.

PubMed

Kuiper, Gerhardus J A J M; Houben, Rik; Wetzels, Rick J H; Verhezen, Paul W M; Oerle, Rene van; Ten Cate, Hugo; Henskens, Yvonne M C; Lancé, Marcus D

2017-11-01

Low platelet counts and hematocrit levels hinder whole blood point-of-care testing of platelet function. Thus far, no reference ranges for MEA (multiple electrode aggregometry) and PFA-100 (platelet function analyzer 100) devices exist for low ranges. Through dilution methods of volunteer whole blood, platelet function at low ranges of platelet count and hematocrit levels was assessed on MEA for four agonists and for PFA-100 in two cartridges. Using (multiple) regression analysis, 95% reference intervals were computed for these low ranges. Low platelet counts affected MEA in a positive correlation (all agonists showed r 2 ≥ 0.75) and PFA-100 in an inverse correlation (closure times were prolonged with lower platelet counts). Lowered hematocrit did not affect MEA testing, except for arachidonic acid activation (ASPI), which showed a weak positive correlation (r 2 = 0.14). Closure time on PFA-100 testing was inversely correlated with hematocrit for both cartridges. Regression analysis revealed different 95% reference intervals in comparison with originally established intervals for both MEA and PFA-100 in low platelet or hematocrit conditions. Multiple regression analysis of ASPI and both tests on the PFA-100 for combined low platelet and hematocrit conditions revealed that only PFA-100 testing should be adjusted for both thrombocytopenia and anemia. 95% reference intervals were calculated using multiple regression analysis. However, coefficients of determination of PFA-100 were poor, and some variance remained unexplained. Thus, in this pilot study using (multiple) regression analysis, we could establish reference intervals of platelet function in anemia and thrombocytopenia conditions on PFA-100 and in thrombocytopenia conditions on MEA.

Robust regression on noisy data for fusion scaling laws

DOE Office of Scientific and Technical Information (OSTI.GOV)

Verdoolaege, Geert, E-mail: geert.verdoolaege@ugent.be; Laboratoire de Physique des Plasmas de l'ERM - Laboratorium voor Plasmafysica van de KMS

2014-11-15

We introduce the method of geodesic least squares (GLS) regression for estimating fusion scaling laws. Based on straightforward principles, the method is easily implemented, yet it clearly outperforms established regression techniques, particularly in cases of significant uncertainty on both the response and predictor variables. We apply GLS for estimating the scaling of the L-H power threshold, resulting in estimates for ITER that are somewhat higher than predicted earlier.

Loneliness among very old Mexican Americans: Findings from the Hispanic established populations epidemiologic studies of the elderly

PubMed Central

Gerst-Emerson, Kerstin; Shovali, Tamar E.; Markides, Kyriakos S.

2015-01-01

Increasing numbers of researchers are finding that loneliness is a significant risk factor for morbidity and mortality, and several of variables have been found to be closely related to the experience of loneliness among elders. However, much of the research has focused on the general older population, with no research to date focusing on minority populations. The objective of this study was to determine the prevalence and the correlates of loneliness among a community-dwelling older Mexican American population. This study used a three-item loneliness scale to determine prevalence of loneliness. Pearson’s correlation and linear regression analyses were used to determine the cross-sectional association between sociodemographic, interpersonal relationship and health variables with the scale. Data used came from the most recent wave (2011) of the Hispanic Established Populations for the Epidemiologic Studies of the Elderly (H-EPESE). A total of 873 Mexican Americans completed the loneliness scale. The age range was from 80 to 102, with a majority (65%) female. The mean score on the scale was 4.05 (range 3–9), indicating relatively low levels of loneliness. Regression results indicate that depressive symptoms, cognitive status, and living alone were significantly associated with higher loneliness scores. Being married and having a confidante were significantly associated with lower loneliness. Age, number of close relatives and frequency of contact were not associated with loneliness. Findings suggest that among community-dwelling Mexican American older adults, loneliness has multiple determinants. Loneliness is a significant public health topic and clinicians should be aware of the various factors that can affect loneliness. PMID:24582944

Process, pattern and scale: hydrogeomorphology and plant diversity in forested wetlands across multiple spatial scales

NASA Astrophysics Data System (ADS)

Alexander, L.; Hupp, C. R.; Forman, R. T.

2002-12-01

Many geodisturbances occur across large spatial scales, spanning entire landscapes and creating ecological phenomena in their wake. Ecological study at large scales poses special problems: (1) large-scale studies require large-scale resources, and (2) sampling is not always feasible at the appropriate scale, and researchers rely on data collected at smaller scales to interpret patterns across broad regions. A criticism of landscape ecology is that findings at small spatial scales are "scaled up" and applied indiscriminately across larger spatial scales. In this research, landscape scaling is addressed through process-pattern relationships between hydrogeomorphic processes and patterns of plant diversity in forested wetlands. The research addresses: (1) whether patterns and relationships between hydrogeomorphic, vegetation, and spatial variables can transcend scale; and (2) whether data collected at small spatial scales can be used to describe patterns and relationships across larger spatial scales. Field measurements of hydrologic, geomorphic, spatial, and vegetation data were collected or calculated for 15- 1-ha sites on forested floodplains of six (6) Chesapeake Bay Coastal Plain streams over a total area of about 20,000 km2. Hydroperiod (day/yr), floodplain surface elevation range (m), discharge (m3/s), stream power (kg-m/s2), sediment deposition (mm/yr), relative position downstream and other variables were used in multivariate analyses to explain differences in species richness, tree diversity (Shannon-Wiener Diversity Index H'), and plant community composition at four spatial scales. Data collected at the plot (400-m2) and site- (c. 1-ha) scales are applied to and tested at the river watershed and regional spatial scales. Results indicate that plant species richness and tree diversity (Shannon-Wiener diversity index H') can be described by hydrogeomorphic conditions at all scales, but are best described at the site scale. Data collected at plot and site scales are tested for spatial heterogeneity across the Chesapeake Bay Coastal Plain using a geostatistical variogram, and multiple regression analysis is used to relate plant diversity, spatial, and hydrogeomorphic variables across Coastal Plain regions and hydrologic regimes. Results indicate that relationships between hydrogeomorphic processes and patterns of plant diversity at finer scales can proxy relationships at coarser scales in some, not all, cases. Findings also suggest that data collected at small scales can be used to describe trends across broader scales under limited conditions.

Visual acuity and contrast sensitivity are two important factors affecting vision-related quality of life in advanced age-related macular degeneration

PubMed Central

Selivanova, Alexandra; Shin, Hyun Joon; Miller, Joan W.; Jackson, Mary Lou

2018-01-01

Purpose Vision loss from age-related macular degeneration (AMD) has a profound effect on vision-related quality of life (VRQoL). The pupose of this study is to identify clinical factors associated with VRQoL using the Rasch- calibrated NEI VFQ-25 scales in bilateral advanced AMD patients. Methods We retrospectively reviewed 47 patients (mean age 83.2 years) with bilateral advanced AMD. Clinical assessment included age, gender, type of AMD, high contrast visual acuity (VA), history of medical conditions, contrast sensitivity (CS), central visual field loss, report of Charles Bonnet Syndrome, current treatment for AMD and Rasch-calibrated NEI VFQ-25 visual function and socioemotional function scales. The NEI VFQ visual function scale includes items of general vision, peripheral vision, distance vision and near vision-related activity while the socioemotional function scale includes items of vision related-social functioning, role difficulties, dependency, and mental health. Multiple regression analysis (structural regression model) was performed using fixed item parameters obtained from the one-parameter item response theory model. Results Multivariate analysis showed that high contrast VA and CS were two factors influencing VRQoL visual function scale (β = -0.25, 95% CI-0.37 to -0.12, p<0.001 and β = 0.35, 95% CI 0.25 to 0.46, p<0.001) and socioemontional functioning scale (β = -0.2, 95% CI -0.37 to -0.03, p = 0.023, and β = 0.3, 95% CI 0.18 to 0.43, p = 0.001). Central visual field loss was not assoicated with either VRQoL visual or socioemontional functioning scale (β = -0.08, 95% CI-0.28 to 0.12,p = 0.44 and β = -0.09, 95% CI -0.03 to 0.16, p = 0.50, respectively). Conclusion In patients with vision impairment secondary to bilateral advanced AMD, high contrast VA and CS are two important factors affecting VRQoL. PMID:29746512

Visual acuity and contrast sensitivity are two important factors affecting vision-related quality of life in advanced age-related macular degeneration.

PubMed

Roh, Miin; Selivanova, Alexandra; Shin, Hyun Joon; Miller, Joan W; Jackson, Mary Lou

2018-01-01

Vision loss from age-related macular degeneration (AMD) has a profound effect on vision-related quality of life (VRQoL). The pupose of this study is to identify clinical factors associated with VRQoL using the Rasch- calibrated NEI VFQ-25 scales in bilateral advanced AMD patients. We retrospectively reviewed 47 patients (mean age 83.2 years) with bilateral advanced AMD. Clinical assessment included age, gender, type of AMD, high contrast visual acuity (VA), history of medical conditions, contrast sensitivity (CS), central visual field loss, report of Charles Bonnet Syndrome, current treatment for AMD and Rasch-calibrated NEI VFQ-25 visual function and socioemotional function scales. The NEI VFQ visual function scale includes items of general vision, peripheral vision, distance vision and near vision-related activity while the socioemotional function scale includes items of vision related-social functioning, role difficulties, dependency, and mental health. Multiple regression analysis (structural regression model) was performed using fixed item parameters obtained from the one-parameter item response theory model. Multivariate analysis showed that high contrast VA and CS were two factors influencing VRQoL visual function scale (β = -0.25, 95% CI-0.37 to -0.12, p<0.001 and β = 0.35, 95% CI 0.25 to 0.46, p<0.001) and socioemontional functioning scale (β = -0.2, 95% CI -0.37 to -0.03, p = 0.023, and β = 0.3, 95% CI 0.18 to 0.43, p = 0.001). Central visual field loss was not assoicated with either VRQoL visual or socioemontional functioning scale (β = -0.08, 95% CI-0.28 to 0.12,p = 0.44 and β = -0.09, 95% CI -0.03 to 0.16, p = 0.50, respectively). In patients with vision impairment secondary to bilateral advanced AMD, high contrast VA and CS are two important factors affecting VRQoL.

How to address data gaps in life cycle inventories: a case study on estimating CO2 emissions from coal-fired electricity plants on a global scale.

PubMed

Steinmann, Zoran J N; Venkatesh, Aranya; Hauck, Mara; Schipper, Aafke M; Karuppiah, Ramkumar; Laurenzi, Ian J; Huijbregts, Mark A J

2014-05-06

One of the major challenges in life cycle assessment (LCA) is the availability and quality of data used to develop models and to make appropriate recommendations. Approximations and assumptions are often made if appropriate data are not readily available. However, these proxies may introduce uncertainty into the results. A regression model framework may be employed to assess missing data in LCAs of products and processes. In this study, we develop such a regression-based framework to estimate CO2 emission factors associated with coal power plants in the absence of reported data. Our framework hypothesizes that emissions from coal power plants can be explained by plant-specific factors (predictors) that include steam pressure, total capacity, plant age, fuel type, and gross domestic product (GDP) per capita of the resident nations of those plants. Using reported emission data for 444 plants worldwide, plant level CO2 emission factors were fitted to the selected predictors by a multiple linear regression model and a local linear regression model. The validated models were then applied to 764 coal power plants worldwide, for which no reported data were available. Cumulatively, available reported data and our predictions together account for 74% of the total world's coal-fired power generation capacity.

SOME STATISTICAL ISSUES RELATED TO MULTIPLE LINEAR REGRESSION MODELING OF BEACH BACTERIA CONCENTRATIONS

EPA Science Inventory

As a fast and effective technique, the multiple linear regression (MLR) method has been widely used in modeling and prediction of beach bacteria concentrations. Among previous works on this subject, however, several issues were insufficiently or inconsistently addressed. Those is...

MULTIPLE REGRESSION MODELS FOR HINDCASTING AND FORECASTING MIDSUMMER HYPOXIA IN THE GULF OF MEXICO

EPA Science Inventory

A new suite of multiple regression models were developed that describe the relationship between the area of bottom water hypoxia along the northern Gulf of Mexico and Mississippi-Atchafalaya River nitrate concentration, total phosphorus (TP) concentration, and discharge. Variabil...

Estimate the contribution of incubation parameters influence egg hatchability using multiple linear regression analysis

PubMed Central

Khalil, Mohamed H.; Shebl, Mostafa K.; Kosba, Mohamed A.; El-Sabrout, Karim; Zaki, Nesma

2016-01-01

Aim: This research was conducted to determine the most affecting parameters on hatchability of indigenous and improved local chickens’ eggs. Materials and Methods: Five parameters were studied (fertility, early and late embryonic mortalities, shape index, egg weight, and egg weight loss) on four strains, namely Fayoumi, Alexandria, Matrouh, and Montazah. Multiple linear regression was performed on the studied parameters to determine the most influencing one on hatchability. Results: The results showed significant differences in commercial and scientific hatchability among strains. Alexandria strain has the highest significant commercial hatchability (80.70%). Regarding the studied strains, highly significant differences in hatching chick weight among strains were observed. Using multiple linear regression analysis, fertility made the greatest percent contribution (71.31%) to hatchability, and the lowest percent contributions were made by shape index and egg weight loss. Conclusion: A prediction of hatchability using multiple regression analysis could be a good tool to improve hatchability percentage in chickens. PMID:27651666

Personality traits as risk factors of depression and anxiety among Japanese students.

PubMed

Matsudaira, Tomomi; Kitamura, Toshinori

2006-01-01

The aim of this study is to examine the effects of personality (temperament and character) on specific depression and specific anxiety. A total of 541 Japanese undergraduates were investigated by using the Temperament and Character Inventory (TCI) and the Hospital Anxiety and Depression (HAD) scale. Hierarchical multiple regression analyses demonstrated that specific depression was predicted by lower Reward-Dependence, Persistence, Self-Directedness, Cooperativeness, and Self-Transcendence; specific anxiety was predicted by higher Novelty-Seeking, Harm-Avoidance, Persistence, and Self-Transcendence, and lower Self-Directedness. Immaturity of Self-Directedness is a risk factor for negative affectivity. Immaturity of all character dimensions is a risk factor for specific depression. The relationship between Harm-Avoidance and depression in previous studies may be linked partly to somatic symptoms that were deliberately eliminated in the HAD scale.

Coach/player relationships in tennis.

PubMed

Prapavessis, H; Gordon, S

1991-09-01

The present study examined the variables that predict coach/athlete compatibility. Compatibility among a sample of 52 elite tennis coach/player dyads was assessed using a sport adapted version of Schutz's (1966) Fundamental Interpersonal Relations Orientation-Behaviour (FIRO-B), a sport adapted version of Fiedler's (1967) Least Preferred Co-worker scale (LPC), and Chelladurai and Saleh's (1980) Leadership Scale for Sport (LSS). Self-ratings of the quality of the interaction were obtained from both coach and athlete. Multiple-regression analyses using self-rating scores as the dependent measure were carried out to determine which variables best predicted the degree of compatibility. The sole inventory that significantly predicted compatibility was the LSS. More specifically, the discrepancy between the athlete's preferences and perceptions on the autocratic dimension was the best predictor. Implications for tennis coaches and recommendations for future research in this area are discussed.

Variations in the temperature and circulation of the atmosphere during the 11-year cycle of solar activity derived from the ERA-Interim reanalysis data

NASA Astrophysics Data System (ADS)

Gruzdev, A. N.

2017-07-01

Using the data of the ERA-Interim reanalysis, we have obtained estimates of changes in temperature, the geopotential and its large-scale zonal harmonics, wind velocity, and potential vorticity in the troposphere and stratosphere of the Northern and Southern hemispheres during the 11-year solar cycle. The estimates have been obtained using the method of multiple linear regression. Specific features of response of the indicated atmospheric parameters to the solar cycle have been revealed in particular regions of the atmosphere for a whole year and depending on the season. The results of the analysis indicate the existence of a reliable statistical relationship of large-scale dynamic and thermodynamic processes in the troposphere and stratosphere with the 11-year solar cycle.

Relationship between postural control and fine motor skills in preterm infants at 6 and 12 months adjusted age.

PubMed

Wang, Tien-Ni; Howe, Tsu-Hsin; Hinojosa, Jim; Weinberg, Sharon L

2011-01-01

We examined the relationship between postural control and fine motor skills of preterm infants at 6 and 12 mo adjusted age. The Alberta Infant Motor Scale was used to measure postural control, and the Peabody Developmental Motor Scales II was used to measure fine motor skills. The data analyzed were taken from 105 medical records from a preterm infant follow-up clinic at an urban academic medical center in south Taiwan. Using multiple regression analyses, we found that the development of postural control is related to the development of fine motor skills, especially in the group of preterm infants with delayed postural control. This finding supports the theoretical assumption of proximal-distal development used by many occupational therapists to guide intervention. Further research is suggested to corroborate findings.

Mean centering, multicollinearity, and moderators in multiple regression: The reconciliation redux.

PubMed

Iacobucci, Dawn; Schneider, Matthew J; Popovich, Deidre L; Bakamitsos, Georgios A

2017-02-01

In this article, we attempt to clarify our statements regarding the effects of mean centering. In a multiple regression with predictors A, B, and A × B (where A × B serves as an interaction term), mean centering A and B prior to computing the product term can clarify the regression coefficients (which is good) and the overall model fit R 2 will remain undisturbed (which is also good).

A Common Mechanism for Resistance to Oxime Reactivation of Acetylcholinesterase Inhibited by Organophosphorus Compounds

DTIC Science & Technology

2013-01-01

application of the Hammett equation with the constants rph in the chemistry of organophosphorus compounds, Russ. Chem. Rev. 38 (1969) 795–811. [13...of oximes and OP compounds and the ability of oximes to reactivate OP- inhibited AChE. Multiple linear regression equations were analyzed using...phosphonate pairs, 21 oxime/ phosphoramidate pairs and 12 oxime/phosphate pairs. The best linear regression equation resulting from multiple regression anal

Novel applications of multitask learning and multiple output regression to multiple genetic trait prediction.

PubMed

He, Dan; Kuhn, David; Parida, Laxmi

2016-06-15

Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait prediction is usually represented as linear regression models. In many cases, for the same set of samples and markers, multiple traits are observed. Some of these traits might be correlated with each other. Therefore, modeling all the multiple traits together may improve the prediction accuracy. In this work, we view the multitrait prediction problem from a machine learning angle: as either a multitask learning problem or a multiple output regression problem, depending on whether different traits share the same genotype matrix or not. We then adapted multitask learning algorithms and multiple output regression algorithms to solve the multitrait prediction problem. We proposed a few strategies to improve the least square error of the prediction from these algorithms. Our experiments show that modeling multiple traits together could improve the prediction accuracy for correlated traits. The programs we used are either public or directly from the referred authors, such as MALSAR (http://www.public.asu.edu/~jye02/Software/MALSAR/) package. The Avocado data set has not been published yet and is available upon request. dhe@us.ibm.com. © The Author 2016. Published by Oxford University Press.

Is the impact of fatigue related to walking capacity and perceived ability in persons with multiple sclerosis? A multicenter study.

PubMed

Dalgas, U; Langeskov-Christensen, M; Skjerbæk, A; Jensen, E; Baert, I; Romberg, A; Santoyo Medina, C; Gebara, B; Maertens de Noordhout, B; Knuts, K; Béthoux, F; Rasova, K; Severijns, D; Bibby, B M; Kalron, A; Norman, B; Van Geel, F; Wens, I; Feys, P

2018-04-15

The relationship between fatigue impact and walking capacity and perceived ability in patients with multiple sclerosis (MS) is inconclusive in the existing literature. A better understanding might guide new treatment avenues for fatigue and/or walking capacity in patients with MS. To investigate the relationship between the subjective impact of fatigue and objective walking capacity as well as subjective walking ability in MS patients. A cross-sectional multicenter study design was applied. Ambulatory MS patients (n = 189, age: 47.6 ± 10.5 years; gender: 115/74 women/men; Expanded Disability Status Scale (EDSS): 4.1 ± 1.8 [range: 0-6.5]) were tested at 11 sites. Objective tests of walking capacity included short walking tests (Timed 25-Foot Walk (T25FW), 10-Metre Walk Test (10mWT) at usual and fastest speed and the timed up and go (TUG)), and long walking tests (2- and 6-Minute Walk Tests (MWT). Subjective walking ability was tested applying the Multiple Sclerosis Walking Scale-12 (MSWS-12). Fatigue impact was measured by the self-reported modified fatigue impact scale (MFIS) consisting of a total score (MFIS total ) and three subscales (MFIS physical , MFIS cognitive and MFIS psychosocial ). Uni- and multivariate regression analysis were performed to evaluate the relation between walking and fatigue impact. MFIS total was negatively related with long (6MWT, r = -0.14, p = 0.05) and short composite (TUG, r = -0.22, p = 0.003) walking measures. MFIS physical showed a significant albeit weak relationship to walking speed in all walking capacity tests (r = -0.22 to -0.33, p < .0001), which persisted in the multivariate linear regression analysis. Subjective walking ability (MSWS-12) was related to MFIS total (r = 0.49, p < 0.0001), as well as to all other subscales of MFIS (r = 0.24-0.63, p < 0.001), showing stronger relationships than objective measures of walking. The physical impact of fatigue is weakly related to objective walking capacity, while general, physical, cognitive and psychosocial fatigue impact are weakly to moderately related to subjective walking ability, when analysed in a large heterogeneous sample of MS patients. Copyright © 2018 Elsevier B.V. All rights reserved.

Relationship between self-focused attention, mindfulness and distress in individuals with auditory verbal hallucinations.

PubMed

Úbeda-Gómez, J; León-Palacios, M G; Escudero-Pérez, S; Barros-Albarrán, M D; López-Jiménez, A M; Perona-Garcelán, S

2015-01-01

The purpose of this study was to investigate the relationships among self-focused attention, mindfulness and distress caused by the voices in psychiatric patients. Fifty-one individuals with a psychiatric diagnosis participated in this study. The Psychotic Symptom Rating Scale (PSYRATS) emotional factor was applied to measure the distress caused by the voices, the Self-Absorption Scale (SAS) was given for measuring the levels of self-focused attention, and the Mindful Attention Awareness Scale (MAAS) was used to measure mindfulness. The results showed that distress caused by the voices correlated positively with self-focused attention (private and public) and negatively with mindfulness. A negative correlation was also found between mindfulness and self-focused attention (private and public). Finally, multiple linear regression analysis showed that public self-focus was the only factor predicting distress caused by the voices. Intervention directed at diminishing public self-focused attention and increasing mindfulness could improve distress caused by the voices.

People’s Preferences of Urban Design Qualities for Walking on a Commercial Street

NASA Astrophysics Data System (ADS)

Ernawati, J.; Surjono; Sudarmo, B. S.

2018-03-01

This research aims to explore people’s preferences of urban design qualities for walking on a commercial street, with Kawi Street located in a commercial neighborhood in the town of Malang Indonesia as the case study. Based on a literature review, this study used eight urban design qualities, i.e., enclosure, legibility, human scale, transparency, complexity, coherence, linkage, and imageability. This study applied a survey research method using a self-administered paper-pencil questionnaire applying two measurement techniques: Likert scale was used to explore people’s evaluations of urban design qualities of the street, while multiple-rating scales were used to measure people’s preference for walking on the street. One hundred and ten people randomly selected as respondents. Regression analysis was employed to explore the influence of urban design qualities on people preference for walking. Results indicated four urban design qualities that affect people’s choice for walking on a commercial street, i.e., transparency, coherence, linkage, and imageability. Implications of the findings will be discussed in the paper.

Simple and multiple linear regression: sample size considerations.

PubMed

Hanley, James A

2016-11-01

The suggested "two subjects per variable" (2SPV) rule of thumb in the Austin and Steyerberg article is a chance to bring out some long-established and quite intuitive sample size considerations for both simple and multiple linear regression. This article distinguishes two of the major uses of regression models that imply very different sample size considerations, neither served well by the 2SPV rule. The first is etiological research, which contrasts mean Y levels at differing "exposure" (X) values and thus tends to focus on a single regression coefficient, possibly adjusted for confounders. The second research genre guides clinical practice. It addresses Y levels for individuals with different covariate patterns or "profiles." It focuses on the profile-specific (mean) Y levels themselves, estimating them via linear compounds of regression coefficients and covariates. By drawing on long-established closed-form variance formulae that lie beneath the standard errors in multiple regression, and by rearranging them for heuristic purposes, one arrives at quite intuitive sample size considerations for both research genres. Copyright © 2016 Elsevier Inc. All rights reserved.

Multiple imputation for cure rate quantile regression with censored data.

PubMed

Wu, Yuanshan; Yin, Guosheng

2017-03-01

The main challenge in the context of cure rate analysis is that one never knows whether censored subjects are cured or uncured, or whether they are susceptible or insusceptible to the event of interest. Considering the susceptible indicator as missing data, we propose a multiple imputation approach to cure rate quantile regression for censored data with a survival fraction. We develop an iterative algorithm to estimate the conditionally uncured probability for each subject. By utilizing this estimated probability and Bernoulli sample imputation, we can classify each subject as cured or uncured, and then employ the locally weighted method to estimate the quantile regression coefficients with only the uncured subjects. Repeating the imputation procedure multiple times and taking an average over the resultant estimators, we obtain consistent estimators for the quantile regression coefficients. Our approach relaxes the usual global linearity assumption, so that we can apply quantile regression to any particular quantile of interest. We establish asymptotic properties for the proposed estimators, including both consistency and asymptotic normality. We conduct simulation studies to assess the finite-sample performance of the proposed multiple imputation method and apply it to a lung cancer study as an illustration. © 2016, The International Biometric Society.

Impact of posterior communicating artery on basilar artery steno-occlusive disease.

PubMed

Hong, J M; Choi, J Y; Lee, J H; Yong, S W; Bang, O Y; Joo, I S; Huh, K

2009-12-01

Acute brainstem infarction with basilar artery (BA) occlusive disease is the most fatal type of all ischaemic strokes. This report investigates the prognostic impact of the posterior communicating artery (PcoA) and whether its anatomy is a safeguard or not. Consecutive patients who had acute brainstem infarction with at least 50% stenosis of BA upon CT angiography (CTA) were studied. The configuration of PcoA was divided into two groups upon CTA: "textbook" group (invisible PcoA with good P1 and P2 segment) and "fetal-variant of PcoA" group (only visible PcoA with absent P1 segment). Baseline demographics, radiological findings and stroke mechanisms were analysed. A multiple regression analysis was performed to predict clinical outcome at 30 days (modified Rankin disability Scale (mRS

Relationship between whole-body tumor burden, clinical phenotype, and quality of life in patients with neurofibromatosis.

PubMed

Merker, Vanessa L; Bredella, Miriam A; Cai, Wenli; Kassarjian, Ara; Harris, Gordon J; Muzikansky, Alona; Nguyen, Rosa; Mautner, Victor F; Plotkin, Scott R

2014-06-01

Patients with neurofibromatosis 1 (NF1), NF2, and schwannomatosis share a predisposition to develop multiple nerve sheath tumors. Previous studies have demonstrated that patients with NF1 and NF2 have reduced quality of life (QOL), but no studies have examined the relationship between whole-body tumor burden and QOL in these patients. We administered a QOL questionnaire (the SF-36) and a visual analog pain scale (VAS) to a previously described cohort of adult neurofibromatosis patients undergoing whole-body MRI. One-sample t-tests were used to compare norm-based SF-36 scores to weighted population means. Spearman correlation coefficients and multiple linear regression analyses controlling for demographic and disease-specific clinical variable were used to relate whole-body tumor volume to QOL scales. Two hundred forty-five patients (142 NF1, 53 NF2, 50 schwannomatosis) completed the study. Subjects showed deficits in selected subscales of the SF-36 compared to adjusted general population means. In bivariate analysis, increased tumor volume was significantly associated with pain in schwannomatosis patients, as measured by the SF-36 bodily pain subscale (rho = -0.287, P = 0.04) and VAS (rho = 0.34, P = 0.02). Regression models for NF2 patients showed a positive relationship between tumor burden and increased pain, as measured by the SF-36 (P = 0.008). Patients with NF1, NF2, and schwannomatosis suffer from reduced QOL, although only pain shows a clear relationship to patient's overall tumor burden. These findings suggest that internal tumor volume is not a primary contributor to QOL and emphasize the need for comprehensive treatment approaches that go beyond tumor-focused therapies such as surgery by including psychosocial interventions. © 2014 Wiley Periodicals, Inc.

Psychosocial correlates of perceived stress among undergraduate medical students in Nigeria

PubMed Central

Thomas, Ibironke F.; Omoaregba, Joyce O.; Okogbenin, Esther O.; Okonoda, Kingsley M.; Ibrahim, Abdu W.; Salihu, Auwal S.; Oshodi, Yewande O.; Orovwigho, Andrew; Odinka, Paul C.; Eze, George O.; Onyebueke, Godwin C.; Aweh, Benjamin E.

2017-01-01

Objectives To assess the prevalence and factors associated with perceived stress among medical students. Methods A cross-sectional study of students (n=623) selected across eight medical schools in Nigeria. A structured questionnaire obtained socio-demographic characteristics, alcohol use (Alcohol Use Disorders Identification Test), other psychoactive drug use (Drug Abuse Screening Test), anxiety/depression symptoms (Hospital Anxiety Depression Scale) and stress (Perceived Medical School Stress Scale). We performed bivariate analysis using the chi-squared test, t-test and one-way ANOVA, with multiple regression analysis for multivariate testing in analysing the data.  Results Most students reported experiencing medical school stress. Female participants were more likely to perceive medical school as competitive (t(621)=1.17, p=0.003), less likely to see medical school as a threat (t(621)=-2.70, p=0.01) or worry about finances (t(621)=-4.80, p=0.001). Nearly a quarter; 21.3% (n=133) and 28.6% (n=178) reported depression and anxiety symptoms respectively. Approximately 4.2% (n=26) were dependent on alcohol, while 14.1% (n=88) had ‘low-risk use’ for other psychoactive substances. In the multiple regression model, lack of finance (B=2.881, p=0.001), weak adherence to religious faith (B=2.376, p=0.001), anxiety symptoms (B=-2.231, p=0.002), problematic alcohol use (B=5.196, p=0.001) and choice of study influenced by parents (B=-3.105, p=0.001) were predictors of greater perceived stress. Conclusions Medical students in Nigeria report high levels of stress. Incorporating stress reduction strategies in the medical curriculum, and the input of students in providing feedback regarding the methods and styles of undergraduate medical education is required.  PMID:29083991

Structural equation model of factors related to quality of life for community-dwelling schizophrenic patients in Japan

PubMed Central

2014-01-01

Background This study aimed to clarify how community mental healthcare systems can be improved. Methods We included 79 schizophrenic patients, aged 20 to 80 years, residing in the Tokyo metropolitan area who regularly visited rehabilitation facilities offering assistance to psychiatric patients and were receiving treatment on an outpatient basis. No subjects had severe cognitive disorders or were taking medication with side effects that could prevent the completion of questionnaires. Questionnaires included items related to quality of life, self-efficacy, self-esteem, psychosis based on the Behavior and Symptom Identification Scale, health locus of control, and socio-demographic factors. We performed multiple linear regression analysis with quality of life as the dependent variable and, based on covariance structural analysis, evaluated the goodness of fit of the resulting structural equations models. Results Self-efficacy, self-esteem, and degree of psychosis significantly impacted quality of life. Marital status, age, and types of medications also influenced quality of life. Multiple linear regression analysis revealed psychiatric symptoms (Behavior and Symptom Identification Scale-32 [daily living and role functioning] (Beta = −0.537, p < 0.001) and self-efficacy (Beta = 0.249, p < 0.05) to be predictors of total quality of life score. Based on covariance structural analysis, the resulting model was found to exhibit reasonable goodness of fit. Conclusions Self-efficacy had an especially strong and direct impact on QOL. Therefore, it is important to provide more positive feedback to patients, provide social skills training based on cognitive behavioral therapy, and engage patients in role playing to improve self-efficacy and self-concept. PMID:25101143

Direct and indirect climate controls predict heterogeneous early-mid 21st century wildfire burned area across western and boreal North America

PubMed Central

Falk, Donald A.; Westerling, Anthony L.; Swetnam, Thomas W.

2017-01-01

Predicting wildfire under future conditions is complicated by complex interrelated drivers operating across large spatial scales. Annual area burned (AAB) is a useful index of global wildfire activity. Current and antecedent seasonal climatic conditions, and the timing of snowpack melt, have been suggested as important drivers of AAB. As climate warms, seasonal climate and snowpack co-vary in intricate ways, influencing fire at continental and sub-continental scales. We used independent records of seasonal climate and snow cover duration (last date of permanent snowpack, LDPS) and cell-based Structural Equation Models (SEM) to separate direct (climatic) and indirect (snow cover) effects on relative changes in AAB under future climatic scenarios across western and boreal North America. To isolate seasonal climate variables with the greatest effect on AAB, we ran multiple regression models of log-transformed AAB on seasonal climate variables and LDPS. We used the results of multiple regressions to project future AAB using GCM ensemble climate variables and LDPS, and validated model predictions with recent AAB trends. Direct influences of spring and winter temperatures on AAB are larger and more widespread than the indirect effect mediated by changes in LDPS in most areas. Despite significant warming trends and reductions in snow cover duration, projected responses of AAB to early-mid 21st century are heterogeneous across the continent. Changes in AAB range from strongly increasing (one order of magnitude increases in AAB) to moderately decreasing (more than halving of baseline AAB). Annual wildfire area burned in coming decades is likely to be highly geographically heterogeneous, reflecting interacting regional and seasonal climate drivers of fire occurrence and spread. PMID:29244839

Determinants of health-related quality of life in international graduate students.

PubMed

Ogunsanya, Motolani E; Bamgbade, Benita A; Thach, Andrew V; Sudhapalli, Poojee; Rascati, Karen L

2018-04-01

International graduate students often experience additional levels of stress due to acculturation. Given the impact of stress on health outcomes (both physical and mental), this study examined the health-related quality of life (HRQoL) in international graduate students to determine its association with acculturative stress, perceived stress, and use of coping mechanisms. A cross-sectional, self-administered survey was designed and sent to 38 student chapters within the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) student network. HRQoL [physical component summary (PCS) and mental component summary (MCS)] was measured using the 12-item Short Form (SF-12) while coping mechanisms were assessed using the Brief COPE Scale. Acculturative and perceived stress were assessed using the Acculturative Stress Scale for International students [ASSIS] and Graduate Stress Inventory-Revised (GSI-R), respectively. Demographic and personal information (e.g. age, religion) were also collected. Descriptive statistics (mean ± SD and frequency) and hierarchical multiple regression analysis were conducted. The average PCS and MCS were 60 ± 9 and 44 ± 13, respectively, indicating that while the physical health was above the United States (US) general population norm (50), mental health scores were lower. Findings from the hierarchical multiple regression showed that perceived and acculturative stress significantly predicted mental health. Acculturative stress was also a significant predictor of physical health. The results from this study support the hypothesis that international students in the US experience both perceived and acculturative stress that significantly impacts their HRQoL. Universities should consider providing education on stress reduction techniques to improve the health of international graduate students. Copyright © 2018 Elsevier Inc. All rights reserved.

Growing old with fibromyalgia: factors that predict physical function.

PubMed

Torma, Linda M; Houck, Gail M; Wagnild, Gail M; Messecar, Deborah; Jones, Kim Dupree

2013-01-01

Fibromyalgia, a persistent, widespread pain condition, significantly limits physical function, threatening an older adult's health and ability to live independently. The aim of the study was to identify predictors of physical function in older adults living with fibromyalgia and to examine the influence of resilience on the relationship between fibromyalgia pain and physical function. This was a descriptive correlational, cross-sectional design using mailed questionnaires to analyze relationships between health-related variables and physical function in a convenience sample of community-dwelling older adults diagnosed with fibromyalgia (n = 224; age M = 62.1 years, SD = 6.75 years). Multiple regression was used to identify a priori predictors of physical function; hierarchical multiple regression was used to examine resilience as a moderator of pain and physical function. The sample was predominantly women, Caucasian, married, well educated, had moderate levels of income and tangible social support, and had low levels of physical function. Three-fourths were overweight or obese. Despite impaired physical function (Late Life Function and Disability Index, M = 51.5/100, SD = 9) and moderate levels of pain (Numeric Rating Scale, M = 5.47/10, SD = 2.6), resilience was moderately high (Resilience Scale, M = 137/175, SD = 20). An eight-variable disablement-based model accounted for 48% of variance in physical function: age, income, education, depressive symptoms, body mass index, and physical activity accounted for 31%; pain added 14%; and resilience contributed an additional 3%. Resilience was not a moderator of fibromyalgia pain and physical function; resilience did contribute uniquely to physical function variance. Resilience, a novel variable in fibromyalgia research, was a unique predictor of physical function. Further research is needed to learn more about the relationships between resilience, fibromyalgia impact, and the aging process.

Psychosocial correlates of perceived stress among undergraduate medical students in Nigeria.

PubMed

James, Bawo O; Thomas, Ibironke F; Omoaregba, Joyce O; Okogbenin, Esther O; Okonoda, Kingsley M; Ibrahim, Abdu W; Salihu, Auwal S; Oshodi, Yewande O; Orovwigho, Andrew; Odinka, Paul C; Eze, George O; Onyebueke, Godwin C; Aweh, Benjamin E

2017-10-26

To assess the prevalence and factors associated with perceived stress among medical students. A cross-sectional study of students (n=623) selected across eight medical schools in Nigeria. A structured questionnaire obtained socio-demographic characteristics, alcohol use (Alcohol Use Disorders Identification Test), other psychoactive drug use (Drug Abuse Screening Test), anxiety/depression symptoms (Hospital Anxiety Depression Scale) and stress (Perceived Medical School Stress Scale). We performed bivariate analysis using the chi-squared test, t-test and one-way ANOVA, with multiple regression analysis for multivariate testing in analysing the data. Most students reported experiencing medical school stress. Female participants were more likely to perceive medical school as competitive (t (621) =1.17, p=0.003), less likely to see medical school as a threat (t (621) =-2.70, p=0.01) or worry about finances (t (621) =-4.80, p=0.001). Nearly a quarter; 21.3% (n=133) and 28.6% (n=178) reported depression and anxiety symptoms respectively. Approximately 4.2% (n=26) were dependent on alcohol, while 14.1% (n=88) had 'low-risk use' for other psychoactive substances. In the multiple regression model, lack of finance (B=2.881, p=0.001), weak adherence to religious faith (B=2.376, p=0.001), anxiety symptoms (B=-2.231, p=0.002), problematic alcohol use (B=5.196, p=0.001) and choice of study influenced by parents (B=-3.105, p=0.001) were predictors of greater perceived stress. Medical students in Nigeria report high levels of stress. Incorporating stress reduction strategies in the medical curriculum, and the input of students in providing feedback regarding the methods and styles of undergraduate medical education is required.

Development and validation of the neck dissection impairment index: a quality of life measure.

PubMed

Taylor, Rodney J; Chepeha, Judith C; Teknos, Theodoros N; Bradford, Carol R; Sharma, Pramod K; Terrell, Jeffrey E; Hogikyan, Norman D; Wolf, Gregory T; Chepeha, Douglas B

2002-01-01

To validate a health-related quality-of-life (QOL) instrument for patients following neck dissection and to identify the factors that affect QOL following neck dissection. Cross-sectional validation study. The outpatient clinic of a tertiary care cancer center. Convenience sample of 54 patients previously treated for head and neck cancer who underwent a selective neck dissection or modified radical neck dissection (64 total neck dissections). Patients had a minimum postoperative convalescence of 11 months. Thirty-two underwent accessory nerve-sparing modified radical neck dissection, and 32 underwent selective neck dissection. A 10-item, self-report instrument, the Neck Dissection Impairment Index (NDII), was developed and validated. Reliability was evaluated with test-retest correlation and internal consistency using the Cronbach alpha coefficient. Convergent validity was assessed using the 36-Item Short-Form Health Survey (SF-36) and the Constant Shoulder Scale, a shoulder function test. Multiple variable regression was used to determine variables that most affected QOL following neck dissection The 10-item NDII test-retest correlation was 0.91 (P<.001) with an internal consistency Cronbach alpha coefficient of.95. The NDII correlated with the Constant Shoulder Scale (r = 0.85, P<.001) and with the SF-36 physical functioning (r = 0.50, P<.001) and role-physical functioning (r = 0.60, P<.001) domains. Using multiple variable regression, the variables that contributed most to QOL score were patient's age and weight, radiation treatment, and neck dissection type. The NDII is a valid, reliable instrument for assessing neck dissection impairment. Patient's age, weight, radiation treatment, and neck dissection type were important factors that affect QOL following neck dissection.

Factors affecting stigma toward suicide and depression: A Korean nationwide study.

PubMed

Park, Soowon; Kim, Min-Ji; Cho, Maeng Je; Lee, Jun-Young

2015-12-01

Suicide attempts and depression are considerably misunderstood by Korean society. Studies regarding factors should provide basic information concerning the factors that should be considered when examining stigmatization. This study aimed to investigate sociodemographic factors related to the social stigma toward people with a history of suicide attempts or depression in a Korean nationwide community sample. Face-to-face interviews were conducted with participants selected via a multi-stage cluster sampling method; 779 respondents completed Link's Perceived Devaluation and Discrimination (PDD) scale to assess the social stigma they attached to suicide attempts, and another 743 completed PDD scale to assess the social stigma they attached to depression. Multiple regression analysis, including socioeconomic and psychiatric variables, was performed to identify the factors predictive of social stigma. Results of multiple regressions revealed that age (β = .12, p = .018), sex (β = .08, p = .038), years of education (β = -.31, p = .006) and history of suicide attempts (β = -.11, p = .009) significantly predicted the degree of stigma toward people who had made suicide attempts, whereas age (β = .15, p = .003) and education (β = -.40, p = .001) also predicted the social stigma toward people with depression, sex and history of a depressive episode did not. Older men with less education and no experience with suicide perceived suicide attempts more negatively. Similarly, older people with less education placed a greater stigma on people suffering from depression. These results suggest that greater access to higher education may reduce stigma toward people with mental illness. © The Author(s) 2015.

Quality of life in multiple sclerosis (MS) and role of fatigue, depression, anxiety, and stress: A bicenter study from north of Iran.

PubMed

Salehpoor, Ghasem; Rezaei, Sajjad; Hosseininezhad, Mozaffar

2014-11-01

Although studies have demonstrated significant negative relationships between quality of life (QOL), fatigue, and the most common psychological symptoms (depression, anxiety, stress), the main ambiguity of previous studies on QOL is in the relative importance of these predictors. Also, there is lack of adequate knowledge about the actual contribution of each of them in the prediction of QOL dimensions. Thus, the main objective of this study is to assess the role of fatigue, depression, anxiety, and stress in relation to QOL of multiple sclerosis (MS) patients. One hundred and sixty-two MS patients completed the questionnaire on demographic variables, and then they were evaluated by the Persian versions of Short-Form Health Survey Questionnaire (SF-36), Fatigue Survey Scale (FSS), and Depression, Anxiety, Stress Scale-21 (DASS-21). Data were analyzed by Pearson correlation coefficient and hierarchical regression. Correlation analysis showed a significant relationship between QOL elements in SF-36 (physical component summary and mental component summary) and depression, fatigue, stress, and anxiety (P < 0.01). Hierarchical regression analysis indicated that among the predictor variables in the final step, fatigue, depression, and anxiety were identified as the physical component summary predictor variables. Anxiety was found to be the most powerful predictor variable amongst all (β = -0.46, P < 0.001). Furthermore, results have shown depression as the only significant mental component summary predictor variable (β = -0.39, P < 0.001). This study has highlighted the role of anxiety, fatigue, and depression in physical dimensions and the role of depression in psychological dimensions of the lives of MS patients. In addition, the findings of this study indirectly suggest that psychological interventions for reducing fatigue, depression, and anxiety can lead to improved QOL of MS patients.

Pain in patients with transverse myelitis and its relationship to aquaporin 4 antibody status.

PubMed

Kong, Yazhuo; Okoruwa, Helen; Revis, Jon; Tackley, George; Leite, Maria Isabel; Lee, Michael; Tracey, Irene; Palace, Jacqueline

2016-09-15

Pain in transverse myelitis has been poorly studied. The aim of the study was to investigate the relationship between transverse myelitis related pain and disability, quality of life, anxiety and depression, cognitive-affective states in neuromyelitis optica (NMO) patients and aquaporin4 antibody status (AQP4-Ab +ve as positive and AQP4-Ab -ve as negative). Transverse myelitis patients (44 in total; 29 AQP4-Ab +ve and 15 AQP4-Ab -ve) completed questionnaires including Pain Severity Index (PSI), Pain Catastrophising Scale (PCS), Hospital Anxiety and Depression Scale (HADS), Short Form-36 quality of life (SF-36 QOL). Clinical details such as disability, gender, age and spinal cord lesion type (short or long lesion) were noted. Correlation and multiple linear regression tests were performed using these clinical scores. Pain was found to be correlated strongly with quality of life in both groups but only correlated with disability in the AQP4-Ab +ve group. PCS, HADS and EDMUS were found to be highly correlated with pain severity using partial correlation, however, a stronger relationship between pain severity and PCS was found in the AQP4-Ab -ve group. Multiple regression analysis showed that pain severity was the most important factor for quality of life but not disability or anxiety and depression symptoms in the whole patient group. We confirm that pain is an important symptom of transverse myelitis and has more influence on quality of life than disability despite health services being predominantly focused on the latter. There may be different factors associated with pain between AQP4-Ab +ve and -ve patients. Copyright © 2016 Elsevier B.V. All rights reserved.

Well-Being and Functioning at Work Following Thefts and Robberies: A Comparative Study

PubMed Central

Setti, Ilaria; van der Velden, Peter G.; Sommovigo, Valentina; Ferretti, Maria S.; Giorgi, Gabriele; O'Shea, Deirdre; Argentero, Piergiorgio

2018-01-01

Thefts and robberies may be traumatizing experiences for employees. The aim of this study is to explore to what extent experiencing robberies and/or thefts at work affect workers' mental health, coping-self-efficacy, social support seeking, workload and job satisfaction. Drawing on Conservation of Resources theory, this research contributes to our understanding of the psychological sequelae of robbery and theft for employees working in small businesses. The few studies on the effects of robberies and thefts in the past have predominantly focused on bank employees. A sample of Italian tobacconists and jewelers completed an anonymous self-report questionnaire examining the experience of robbery and/or theft, social support seeking (Coping Orientation to Problem Experienced scale, COPE-IV), psycho-somatic well-being (General Health Questionnaire, GHQ-12), job satisfaction (a single item). Victims of thefts and/or robberies reported their PTSD symptoms (Impact of Event- Revised 6, IES-R-6) and trauma-related coping self-efficacy (Coping Self-Efficacy scale, CSE-7), based on the last event (N = 319). Descriptive analyses, ANOVA, ANCOVA and multiple regressions analyses have been carried out. The results indicated that victims of thefts and robberies experienced greater workload, higher psycho-physical complaints and greater tendency to seek social support in comparison with their non-affected counterparts. They additionally experienced more post-traumatic symptomatology and perceived lower coping self-efficacy, when compared to those who experienced thefts “only.” Multiple regression analyses revealed that CSE was positively related to job satisfaction, although the presence of psycho-physical symptoms was the main predictor of job satisfaction among both non-affected and affected employees. PTSD was not an independent predictor of job satisfaction. In sum, robberies and/or thefts exposure undermines differently workers' well-being. PMID:29515488

Organizational culture in cardiovascular care in Chinese hospitals: a descriptive cross-sectional study.

PubMed

Yin, Emily S; Downing, Nicholas S; Li, Xi; Singer, Sara J; Curry, Leslie A; Li, Jing; Krumholz, Harlan M; Jiang, Lixin

2015-12-21

Organizational learning, the process by which a group changes its behavior in response to newly acquired knowledge, is critical to outstanding organizational performance. In hospitals, strong organizational learning culture is linked with improved health outcomes for patients. This study characterizes the organizational learning culture of hospitals in China from the perspective of a cardiology service. Using a modified Abbreviated Learning Organization Survey (27 questions), we characterized organizational learning culture in a nationally representative sample of 162 Chinese hospitals, selecting 2 individuals involved with cardiovascular care at each hospital. Responses were analyzed at the hospital level by calculating the average of the two responses to each question. Responses were categorized as positive if they were 5+ on a 7-point scale or 4+ on a 5-point scale. Univariate and multiple regression analyses were used to assess the relationship between selected hospital characteristics and perceptions of organizational learning culture. Of the 324 participants invited to take the survey, 316 responded (98 % response rate). Perceptions of organizational learning culture varied among items, among domains, and both among and within hospitals. Overall, the median proportion of positive responses was 82 % (interquartile range = 59 % to 93 %). "Training," "Performance Monitoring," and "Leadership that Reinforces Learning" were characterized as the most favorable domains, while "Time for Reflection" was the least favorable. Multiple regression analyses showed that region was the only factor significantly correlated with overall positive response rate. This nationally representative survey demonstrated variation in hospital organizational learning culture among hospitals in China. The variation was not substantially explained by hospital characteristics. Organizational learning culture domains with lower positive response rates reveal important areas for improvement.

Multiscale characterization and prediction of monsoon rainfall in India using Hilbert-Huang transform and time-dependent intrinsic correlation analysis

NASA Astrophysics Data System (ADS)

Adarsh, S.; Reddy, M. Janga

2017-07-01

In this paper, the Hilbert-Huang transform (HHT) approach is used for the multiscale characterization of All India Summer Monsoon Rainfall (AISMR) time series and monsoon rainfall time series from five homogeneous regions in India. The study employs the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) for multiscale decomposition of monsoon rainfall in India and uses the Normalized Hilbert Transform and Direct Quadrature (NHT-DQ) scheme for the time-frequency characterization. The cross-correlation analysis between orthogonal modes of All India monthly monsoon rainfall time series and that of five climate indices such as Quasi Biennial Oscillation (QBO), El Niño Southern Oscillation (ENSO), Sunspot Number (SN), Atlantic Multi Decadal Oscillation (AMO), and Equatorial Indian Ocean Oscillation (EQUINOO) in the time domain showed that the links of different climate indices with monsoon rainfall are expressed well only for few low-frequency modes and for the trend component. Furthermore, this paper investigated the hydro-climatic teleconnection of ISMR in multiple time scales using the HHT-based running correlation analysis technique called time-dependent intrinsic correlation (TDIC). The results showed that both the strength and nature of association between different climate indices and ISMR vary with time scale. Stemming from this finding, a methodology employing Multivariate extension of EMD and Stepwise Linear Regression (MEMD-SLR) is proposed for prediction of monsoon rainfall in India. The proposed MEMD-SLR method clearly exhibited superior performance over the IMD operational forecast, M5 Model Tree (MT), and multiple linear regression methods in ISMR predictions and displayed excellent predictive skill during 1989-2012 including the four extreme events that have occurred during this period.

Quality of life in children with infantile hemangioma: a case control study.

PubMed

Wang, Chuan; Li, Yanan; Xiang, Bo; Xiong, Fei; Li, Kai; Yang, Kaiying; Chen, Siyuan; Ji, Yi

2017-11-16

Infantile hemangioma (IH) is the most common vascular tumor in children. It is controversial whether IHs has effects on the quality of life (QOL) in patients of whom IH poses no threat or potential for complication. Thus, we conducted this study to evaluate the q QOL in patients with IH and find the predictors of poor QOL. The PedsQL 4.0 Genetic Core Scales and the PedsQL family information form were administered to parents of children with IH and healthy children both younger than 2-year-old. The quality-of-life instrument for IH (IH-QOL) and the PedsQL 4.0 family impact module were administered to parents of children with IH. We compared the PedsQL 4.0 Genetic Core Scales (GCIS) scores of the two groups. Multiple step-wise regression analysis was used to determine factors that influenced QOL in children with IH and their parents. Except for physical symptom, we found no significant difference in GCIS between patient group and healthy group (P = 0.409). The internal reliability of IH-QOL was excellent with the Cronbach's alpha coefficient for summary scores being 0.76. Multiple step-wise regression analysis showed that the predictors of poor IH-QOL total scores were hemangioma size, location, and mother's education level. The predictors of poor FIM total scores were hemangioma location and father's education level. The predictors of poor GCIS total scores were children's age, hemangioma location and father's education level. The findings support the feasibility and reliability of the Chinese version of IH-QOL to evaluate the QOL in children with IH and their parents. Hemangioma size, location and education level of mother are important impact factors for QOL in children with IH and their parents.

Direct and indirect climate controls predict heterogeneous early-mid 21st century wildfire burned area across western and boreal North America.

PubMed

Kitzberger, Thomas; Falk, Donald A; Westerling, Anthony L; Swetnam, Thomas W

2017-01-01

Predicting wildfire under future conditions is complicated by complex interrelated drivers operating across large spatial scales. Annual area burned (AAB) is a useful index of global wildfire activity. Current and antecedent seasonal climatic conditions, and the timing of snowpack melt, have been suggested as important drivers of AAB. As climate warms, seasonal climate and snowpack co-vary in intricate ways, influencing fire at continental and sub-continental scales. We used independent records of seasonal climate and snow cover duration (last date of permanent snowpack, LDPS) and cell-based Structural Equation Models (SEM) to separate direct (climatic) and indirect (snow cover) effects on relative changes in AAB under future climatic scenarios across western and boreal North America. To isolate seasonal climate variables with the greatest effect on AAB, we ran multiple regression models of log-transformed AAB on seasonal climate variables and LDPS. We used the results of multiple regressions to project future AAB using GCM ensemble climate variables and LDPS, and validated model predictions with recent AAB trends. Direct influences of spring and winter temperatures on AAB are larger and more widespread than the indirect effect mediated by changes in LDPS in most areas. Despite significant warming trends and reductions in snow cover duration, projected responses of AAB to early-mid 21st century are heterogeneous across the continent. Changes in AAB range from strongly increasing (one order of magnitude increases in AAB) to moderately decreasing (more than halving of baseline AAB). Annual wildfire area burned in coming decades is likely to be highly geographically heterogeneous, reflecting interacting regional and seasonal climate drivers of fire occurrence and spread.

Resilience and Associated Factors among Mainland Chinese Women Newly Diagnosed with Breast Cancer.

PubMed

Wu, Zijing; Liu, Ye; Li, Xuelian; Li, Xiaohan

2016-01-01

Resilience is the individual's ability to bounce back from trauma. It has been studied for some time in the U.S., but few studies in China have addressed this important construct. In mainland China, relatively little is known about the resilience of patients in clinical settings, especially among patients with breast cancer. In this study, we aimed to evaluate the level of resilience and identify predictors of resilience among mainland Chinese women newly diagnosed with breast cancer. A cross-sectional descriptive study was conducted with 213 mainland Chinese women newly diagnosed with breast cancer between November 2014 and June 2015. Participants were assessed with the Connor-Davidson Resilience Scale (CD-RISC), Social Support Rating Scale (SSRS), Medical Coping Modes Questionnaire (MCMQ, including 3 subscales: confrontation, avoidance, and acceptance-resignation), Herth Hope Index (HHI), and demographic and disease-related information. Descriptive statistics, bivariate analyses and multiple stepwise regression were conducted to explore predictors for resilience. The average score for CD-RISC was 60.97, ranging from 37 to 69. Resilience was positively associated with educational level, family income, time span after diagnosis, social support, confrontation, avoidance, and hope. However, resilience was negatively associated with age, body mass index (BMI), and acceptance-resignation. Multiple stepwise regression analysis indicated that hope (β = 0.343, P<0.001), educational level of junior college or above (β = 0.272, P<0.001), educational level of high school (β = 0.235, P<0.001), avoidance (β = 0.220, P<0.001), confrontation (β = 0.187, P = 0.001), and age (β = -0.108, P = 0.037) significantly affected resilience and explained 50.1% of the total variance in resilience. Women with newly diagnosed breast cancer from mainland China demonstrated particularly low resilience level, which was predicted by hope educational level, avoidance, confrontation, and age.

An Examination of Postsecondary Faculty and the Extent of Critical Reading Taught in 100-Level Introductory Biology and American History Courses in Publicly Funded Two-Year and Four-Year Pennsylvania Institutions

NASA Astrophysics Data System (ADS)

Sand, Dianna

This research examined the responses of postsecondary faculty on a critical reading inventory. The research is quantitative, non-experimental, and incorporates a multiple regression model in the analyses. Three research questions guided this study: (1) By institution type: To what degree does institution type predict the extent to which postsecondary faculty teach critical reading as measured by the Reading Goals Inventory (Jones, 1996)? (2) By faculty status: To what degree does faculty status predict the extent to which postsecondary faculty teach critical reading as measured by the Reading Goals Inventory (Jones, 1996)? (3) By disciplinary area: To what degree does disciplinary area predict the extent to which postsecondary faculty teach critical reading as measured by the Reading Goals Inventory (Jones, 1996)? Faculty from 28 Pennsylvania postsecondary institutions participated in this study. Faculty respondents taught 100-level introductory biology or American history courses either part-time or full-time at Pennsylvania community colleges or Pennsylvania State System of Higher Education (PASSHE) universities. Fifty-four faculty respondents completed the Reading Goals Inventory (Jones, 1996). The researcher conducted multiple regression analyses using a hierarchical method. Predictor variables included Institution Type, Faculty Status, and Disciplinary Area; criterion or outcome variables included seven sub-scales of the critical reading inventory. In this study, Institution Type and Faculty Status were not significant predictors. Disciplinary Area was a consistent significant predictor of the amount of critical reading taught as measured in the Interpretation, Analysis, Evaluation, and Reflection sub-scales of the Reading Goals Inventory (Jones, 1996).

Evidence for early neurodegeneration in the cervical cord of patients with primary progressive multiple sclerosis

PubMed Central

Schneider, Torben; Solanky, Bhavana S.; Yiannakas, Marios C.; Altmann, Dan R.; Wheeler-Kingshott, Claudia A. M.; Peters, Amy L.; Day, Brian L.; Thompson, Alan J.; Ciccarelli, Olga

2015-01-01

Spinal neurodegeneration is an important determinant of disability progression in patients with primary progressive multiple sclerosis. Advanced imaging techniques, such as single-voxel 1H-magnetic resonance spectroscopy and q-space imaging, have increased pathological specificity for neurodegeneration, but are challenging to implement in the spinal cord and have yet to be applied in early primary progressive multiple sclerosis. By combining these imaging techniques with new clinical measures, which reflect spinal cord pathology more closely than conventional clinical tests, we explored the potential for spinal magnetic resonance spectroscopy and q-space imaging to detect early spinal neurodegeneration that may be responsible for clinical disability. Data from 21 patients with primary progressive multiple sclerosis within 6 years of disease onset, and 24 control subjects were analysed. Patients were clinically assessed on grip strength, vibration perception thresholds and postural stability, in addition to the Expanded Disability Status Scale, Nine Hole Peg Test, Timed 25-Foot Walk Test, Multiple Sclerosis Walking Scale-12, and Modified Ashworth Scale. All subjects underwent magnetic resonance spectroscopy and q-space imaging of the cervical cord and conventional brain and spinal magnetic resonance imaging at 3 T. Multivariate analyses and multiple regression models were used to assess the differences in imaging measures between groups and the relationship between magnetic resonance imaging measures and clinical scores, correcting for age, gender, spinal cord cross-sectional area, brain T2 lesion volume, and brain white matter and grey matter volume fractions. Although patients did not show significant cord atrophy when compared with healthy controls, they had significantly lower total N-acetyl-aspartate (mean 4.01 versus 5.31 mmol/l, P = 0.020) and glutamate-glutamine (mean 4.65 versus 5.93 mmol/l, P = 0.043) than controls. Patients showed an increase in q-space imaging-derived indices of perpendicular diffusivity in both the whole cord and major columns compared with controls (P < 0.05 for all indices). Lower total N-acetyl-aspartate was associated with higher disability, as assessed by the Expanded Disability Status Scale (coefficient = −0.41, 0.01 < P < 0.05), Modified Ashworth Scale (coefficient = −3.78, 0.01 < P < 0.05), vibration perception thresholds (coefficient = −4.37, P = 0.021) and postural sway (P < 0.001). Lower glutamate-glutamine predicted increased postural sway (P = 0.017). Increased perpendicular diffusivity in the whole cord and columns was associated with increased scores on the Modified Ashworth Scale, vibration perception thresholds and postural sway (P < 0.05 in all cases). These imaging findings indicate reduced structural integrity of neurons, demyelination, and abnormalities in the glutamatergic pathways in the cervical cord of early primary progressive multiple sclerosis, in the absence of extensive spinal cord atrophy. The observed relationship between imaging measures and disability suggests that early spinal neurodegeneration may underlie clinical impairment, and should be targeted in future clinical trials with neuroprotective agents to prevent the development of progressive disability. PMID:25863355

Lower urinary tract symptoms and erectile dysfunction associated with depression among Japanese patients with late-onset hypogonadism symptoms.

PubMed

Takao, Tetsuya; Tsujimura, Akira; Okuda, Hidenobu; Yamamoto, Keisuke; Fukuhara, Shinichiro; Matsuoka, Yasuhiro; Miyagawa, Yasushi; Nonomura, Norio; Okuyama, Akihiko

2011-06-01

The aim of this study was to investigate the relation between lower urinary tract symptoms (LUTS), erectile dysfunction (ED) and depression in Japanese patients with late-onset hypogonadism (LOH) symptoms. The study comprised 87 Japanese patients with LOH symptoms (>27 points on the Aging Males Symptoms Scale). Thirty-four patients were diagnosed as having depression and the remaining 53 patients were diagnosed as not having depression by the Mini International Neuropsychiatric Interview. We compared the International Index of Erectile Function (IIEF) 5, International Prostate Symptom Score (IPSS), IPSS quality-of-life (QOL) index, King's Health Questionnaire (KHQ), endocrinological data, and free uroflow study between depression and non-depression patients and performed multiple logistic regression analysis. IIEF5 scores of depression patients were significantly lower than those of non-depression patients. In KHQ, only the category of general health perceptions was significantly higher in depression patients than non-depression patients. However, IPSS, QOL index, and endocrinological and uroflowmetric data showed no significant difference between the groups. Multiple logistic regression analysis revealed moderate and severe ED to be risk factors for depression. However, LUTS are not related to depression. Moderate and severe ED is correlated with depression, whereas LUTS are not related to depression in Japanese LOH patients.

Examination of the Relationship Between Autonomy and English Achievement as Mediated by Foreign Language Classroom Anxiety.

PubMed

Ghorbandordinejad, Farhad; Ahmadabad, Roghayyeh Moradian

2016-06-01

This study investigated the relationship between autonomy and English language achievement among third-grade high school students as mediated by foreign language classroom anxiety in a city in the north-west of Iran. A sample of 400 students (187 males, and 213 females) was assessed for their levels of autonomy and foreign language anxiety using the Autonomy Questionnaire and Foreign Language Classroom Anxiety Scale (FLCAS), respectively. Participants' scores on their final English exam were also used as the measurement of their English achievement. The results of Pearson correlation revealed a strong correlation between learners' autonomy and their English achievement (r [Formula: see text] .406, n [Formula: see text] 400, [Formula: see text]). Also, foreign language classroom anxiety was found to be significantly and negatively correlated with English achievement (r [Formula: see text] [Formula: see text].472, n [Formula: see text] 400, [Formula: see text]). Hierarchical multiple regression was used to assess the ability of autonomy to predict language learning achievement, after controlling for the influence of anxiety. In sum, the results of hierarchical multiple regressions revealed that foreign language classroom anxiety significantly mediates the relationship between autonomy and English language achievement. Implications for both teachers and learners, and suggestions for further research are provided.

Rigid and flexible control of eating behavior in a college population.

PubMed

Timko, C Alix; Perone, Julie

2005-02-01

The objective of this study was to explore the relationship between rigid control (RC) and flexible control (FC) of eating behavior and their relationship to traditional weight, eating, and affective measurements in a large heterogeneous population. Participants were 639 underweight to obese male and female college students. Multiple regression analyses (MRA) revealed that high RC was associated with high Body Mass Index (BMI) and high Disinhibition (DIS), and high FC was associated with low BMI and low DIS in women. In men, high RC was associated with high BMI and high DIS, whereas FC was not related to BMI or DIS. Multiple regression analyses of BMI on RC and FC in the female subsample revealed that the control variables interact in such a way that the relationship between RC and BMI is stronger when FC is lower. In men, there was no interaction between these variables. This study is the first full replication of Westenhoefer's Gezugeltes Essen und Storbarkeit des Ebetaverhaltens: 2. Auflage. Gottingen: Verlag fur Psychologie () findings regarding RC and FC and their relationship to weight (BMI) and Disinhibition (DIS) in women. This is also the only second study to use the expanded, more reliable versions of the RC and FC scales. Overall, high RC in women and men was associated with greater eating and affective pathology.

Bacterial diversity in saliva and oral health-related conditions: the Hisayama Study

NASA Astrophysics Data System (ADS)

Takeshita, Toru; Kageyama, Shinya; Furuta, Michiko; Tsuboi, Hidenori; Takeuchi, Kenji; Shibata, Yukie; Shimazaki, Yoshihiro; Akifusa, Sumio; Ninomiya, Toshiharu; Kiyohara, Yutaka; Yamashita, Yoshihisa

2016-02-01

This population-based study determined the salivary microbiota composition of 2,343 adult residents of Hisayama town, Japan, using 16S rRNA gene next-generation high-throughput sequencing. Of 550 identified species-level operational taxonomic units (OTUs), 72 were common, in ≥75% of all individuals, as well as in ≥75% of the individuals in the lowest quintile of phylogenetic diversity (PD). These “core” OTUs constituted 90.9 ± 6.1% of each microbiome. The relative abundance profiles of 22 of the core OTUs with mean relative abundances ≥1% were stratified into community type I and community type II by partitioning around medoids clustering. Multiple regression analysis revealed that a lower PD was associated with better conditions for oral health, including a lower plaque index, absence of decayed teeth, less gingival bleeding, shallower periodontal pockets and not smoking, and was also associated with tooth loss. By contrast, multiple Poisson regression analysis demonstrated that community type II, as characterized by a higher ratio of the nine dominant core OTUs, including Neisseria flavescens, was implicated in younger age, lower body mass index, fewer teeth with caries experience, and not smoking. Our large-scale data analyses reveal variation in the salivary microbiome among Japanese adults and oral health-related conditions associated with the salivary microbiome.

Motor Skill Competence and Perceived Motor Competence: Which Best Predicts Physical Activity among Girls?

PubMed

Khodaverdi, Zeinab; Bahram, Abbas; Khalaji, Hassan; Kazemnejad, Anoshirvan

2013-10-01

The main purpose of this study was to determine which correlate, perceived motor competence or motor skill competence, best predicts girls' physical activity behavior. A sample of 352 girls (mean age=8.7, SD=0.3 yr) participated in this study. To assess motor skill competence and perceived motor competence, each child completed the Test of Gross Motor Development-2 and Physical Ability sub-scale of Marsh's Self-Description Questionnaire. Children's physical activity was assessed by the Physical Activity Questionnaire for Older Children. Multiple linear regression model was used to determine whether perceived motor competence or motor skill competence best predicts moderate-to-vigorous self-report physical activity. Multiple regression analysis indicated that motor skill competence and perceived motor competence predicted 21% variance in physical activity (R(2)=0.21, F=48.9, P=0.001), and motor skill competence (R(2)=0.15, ᵝ=0.33, P= 0.001) resulted in more variance than perceived motor competence (R(2)=0.06, ᵝ=0.25, P=0.001) in physical activity. Results revealed motor skill competence had more influence in comparison with perceived motor competence on physical activity level. We suggest interventional programs based on motor skill competence and perceived motor competence should be administered or implemented to promote physical activity in young girls.

The mediator effect of personality traits on the relationship between childhood abuse and depressive symptoms in schizophrenia.

PubMed

Okubo, Ryo; Inoue, Takeshi; Hashimoto, Naoki; Suzukawa, Akio; Tanabe, Hajime; Oka, Matsuhiko; Narita, Hisashi; Ito, Koki; Kako, Yuki; Kusumi, Ichiro

2017-11-01

Previous studies indicated that personality traits have a mediator effect on the relationship between childhood abuse and depressive symptoms in major depressive disorder and nonclinical general adult subjects. In the present study, we aimed to test the hypothesis that personality traits mediate the relationship between childhood abuse and depressive symptoms in schizophrenia. We used the following questionnaires to evaluate 255 outpatients with schizophrenia: the Child Abuse and Trauma Scale, temperament and character inventory, and Patients Health Questionnire-9. Univariate analysis, multiple regression analysis, and structured equation modeling (SEM) were used to analyze the data. The relationship between neglect and sexual abuse and the severity of depressive symptoms was mostly mediated by the personality traits of high harm avoidance, low self-directedness, and low cooperativeness. This finding was supported by the results of stepwise multiple regression analysis and the acceptable fit indices of SEM. Thus, our results suggest that personality traits mediate the relationship between childhood abuse and depressive symptoms in schizophrenia. The present study and our previous studies also suggest that this mediator effect could occur independent of the presence or type of mental disorder. Clinicians should routinely assess childhood abuse history, personality traits, and their effects in schizophrenia. Copyright © 2017. Published by Elsevier B.V.

Undergraduate Student Motivation in Modularized Developmental Mathematics Courses

ERIC Educational Resources Information Center

Pachlhofer, Keith A.

2017-01-01

This study used the Motivated Strategies for Learning Questionnaire in modularized courses at three institutions across the nation (N = 189), and multiple regression was completed to investigate five categories of student motivation that predicted academic success and course completion. The overall multiple regression analysis was significant and…

MULGRES: a computer program for stepwise multiple regression analysis

Treesearch

A. Jeff Martin

1971-01-01

MULGRES is a computer program source deck that is designed for multiple regression analysis employing the technique of stepwise deletion in the search for most significant variables. The features of the program, along with inputs and outputs, are briefly described, with a note on machine compatibility.

Categorical Variables in Multiple Regression: Some Cautions.

ERIC Educational Resources Information Center

O'Grady, Kevin E.; Medoff, Deborah R.

1988-01-01

Limitations of dummy coding and nonsense coding as methods of coding categorical variables for use as predictors in multiple regression analysis are discussed. The combination of these approaches often yields estimates and tests of significance that are not intended by researchers for inclusion in their models. (SLD)

Clinical application of ICF key codes to evaluate patients with dysphagia following stroke

PubMed Central

Dong, Yi; Zhang, Chang-Jie; Shi, Jie; Deng, Jinggui; Lan, Chun-Na

2016-01-01

Abstract This study was aimed to identify and evaluate the International Classification of Functioning (ICF) key codes for dysphagia in stroke patients. Thirty patients with dysphagia after stroke were enrolled in our study. To evaluate the ICF dysphagia scale, 6 scales were used as comparisons, namely the Barthel Index (BI), Repetitive Saliva Swallowing Test (RSST), Kubota Water Swallowing Test (KWST), Frenchay Dysarthria Assessment, Mini-Mental State Examination (MMSE), and the Montreal Cognitive Assessment (MoCA). Multiple regression analysis was performed to quantitate the relationship between the ICF scale and the other 7 scales. In addition, 60 ICF scales were analyzed by the least absolute shrinkage and selection operator (LASSO) method. A total of 21 ICF codes were identified, which were closely related with the other scales. These included 13 codes from Body Function, 1 from Body Structure, 3 from Activities and Participation, and 4 from Environmental Factors. A topographic network map with 30 ICF key codes was also generated to visualize their relationships. The number of ICF codes identified is in line with other well-established evaluation methods. The network topographic map generated here could be used as an instruction tool in future evaluations. We also found that attention functions and biting were critical codes of these scales, and could be used as treatment targets. PMID:27661012

Multiple Imputation of a Randomly Censored Covariate Improves Logistic Regression Analysis.

PubMed

Atem, Folefac D; Qian, Jing; Maye, Jacqueline E; Johnson, Keith A; Betensky, Rebecca A

2016-01-01

Randomly censored covariates arise frequently in epidemiologic studies. The most commonly used methods, including complete case and single imputation or substitution, suffer from inefficiency and bias. They make strong parametric assumptions or they consider limit of detection censoring only. We employ multiple imputation, in conjunction with semi-parametric modeling of the censored covariate, to overcome these shortcomings and to facilitate robust estimation. We develop a multiple imputation approach for randomly censored covariates within the framework of a logistic regression model. We use the non-parametric estimate of the covariate distribution or the semiparametric Cox model estimate in the presence of additional covariates in the model. We evaluate this procedure in simulations, and compare its operating characteristics to those from the complete case analysis and a survival regression approach. We apply the procedures to an Alzheimer's study of the association between amyloid positivity and maternal age of onset of dementia. Multiple imputation achieves lower standard errors and higher power than the complete case approach under heavy and moderate censoring and is comparable under light censoring. The survival regression approach achieves the highest power among all procedures, but does not produce interpretable estimates of association. Multiple imputation offers a favorable alternative to complete case analysis and ad hoc substitution methods in the presence of randomly censored covariates within the framework of logistic regression.

Depression and anxiety in multiple system atrophy.

PubMed

Zhang, L-Y; Cao, B; Zou, Y-T; Wei, Q-Q; Ou, R-W; Zhao, B; Wu, Y; Shang, H-F

2018-01-01

It has been noticed that the patients with multiple system atrophy (MSA) can accompany with depression and anxiety. This study aimed to establish the incidence and determinants of depression and anxiety symptoms in Chinese MSA patients. A total of 237 MSA patients were enrolled in the study. Neuropsychological assessment was performed using Hamilton Depression Rating Scale-24 items and Hamilton Anxiety Rating Scale. We found that 62.0% and 71.7% patients had at least mild depression and anxiety symptoms, respectively. The severity of depression of MSA patients was associated with lower educational years (P=.024), longer disease duration (P<.001), and disease severity (P<.001). The severity of anxiety was associated with increased disease duration (P<.001), disease severity (P=.013), and orthostatic hypotension (P=.005). Binary logistic regression showed the determinants of depression and anxiety were female gender, longer disease duration, and disease severity. Depression and anxiety symptoms are common in patients with MSA. Neurologists should pay attention to depression and anxiety in patients with MSA, especially in female patients and those with longer disease duration and severe disease condition. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The Multicultural Identity Integration Scale (MULTIIS): Developing a comprehensive measure for configuring one's multiple cultural identities within the self.

PubMed

Yampolsky, Maya A; Amiot, Catherine E; de la Sablonnière, Roxane

2016-04-01

The research investigating how one's multiple cultural identities are configured within the self has yet to account for existing cultural identity configurations aside from integration, and for identifying with more than 2 cultural groups at once. The current research addresses these issues by constructing the Multicultural Identity Integration Scale (MULTIIS) to examine 3 different multicultural identity configurations, and their relationship to well-being based on Amiot and colleagues' (2007) cognitive-developmental model of social identity integration (CDSMII). Diverse samples of multicultural individuals completed the MULTIIS along with identity and well-being measures. (Study 1A: N = 407; 1B: N = 310; 2A = 338 and 2A = 254) RESULTS: Reliability and confirmatory factorial analyses (Studies 1A and 2A) all supported the factorial structure of the MULTIIS. Regression analyses (Studies 1B and 2B) confirmed that the integration subscale of the MULTIIS positively predicted well-being, whereas compartmentalization negatively predicted well-being. Categorization was inconsistently related to well-being. These findings support the CDSMII and the usefulness of the MULTIIS measure, and suggest that each identity configuration is uniquely related to well-being outcomes. (c) 2016 APA, all rights reserved).

Can Meditation Influence Quality of Life, Depression, and Disease Outcome in Multiple Sclerosis? Findings from a Large International Web-Based Study

PubMed Central

Levin, Adam B.; Hadgkiss, Emily J.; Weiland, Tracey J.; Marck, Claudia H.; van der Meer, Dania M.; Pereira, Naresh G.; Jelinek, George A.

2014-01-01

Objectives. To explore the association between meditation and health related quality of life (HRQOL), depression, fatigue, disability level, relapse rates, and disease activity in a large international sample of people with multiple sclerosis (MS). Methods. Participants were invited to take part in an online survey and answer questions relating to HRQOL, depression, fatigue, disability, relapse rates, and their involvement in meditation practices. Results. Statistically and potentially clinically significant differences between those who meditated once a week or more and participants who never meditated were present for mean mental health composite (MHC) scores, cognitive function scale, and health perception scale. The MHC results remained statistically significant on multivariate regression modelling when covariates were accounted for. Physical health composite (PHC) scores were higher in those that meditated; however, the differences were probably not clinically significant. Among those who meditated, fewer screened positive for depression, but there was no relationship with fatigue or relapse rate. Those with worsened disability levels were more likely to meditate. Discussion. The study reveals a significant association between meditation, lower risk of depression, and improved HRQOL in people with MS. PMID:25477709

Advanced Statistics for Exotic Animal Practitioners.

PubMed

Hodsoll, John; Hellier, Jennifer M; Ryan, Elizabeth G

2017-09-01

Correlation and regression assess the association between 2 or more variables. This article reviews the core knowledge needed to understand these analyses, moving from visual analysis in scatter plots through correlation, simple and multiple linear regression, and logistic regression. Correlation estimates the strength and direction of a relationship between 2 variables. Regression can be considered more general and quantifies the numerical relationships between an outcome and 1 or multiple variables in terms of a best-fit line, allowing predictions to be made. Each technique is discussed with examples and the statistical assumptions underlying their correct application. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluating construct validity of the second version of the Copenhagen Psychosocial Questionnaire through analysis of differential item functioning and differential item effect.

PubMed

Bjorner, Jakob Bue; Pejtersen, Jan Hyld

2010-02-01

To evaluate the construct validity of the Copenhagen Psychosocial Questionnaire II (COPSOQ II) by means of tests for differential item functioning (DIF) and differential item effect (DIE). We used a Danish general population postal survey (n = 4,732 with 3,517 wage earners) with a one-year register based follow up for long-term sickness absence. DIF was evaluated against age, gender, education, social class, public/private sector employment, and job type using ordinal logistic regression. DIE was evaluated against job satisfaction and self-rated health (using ordinal logistic regression), against depressive symptoms, burnout, and stress (using multiple linear regression), and against long-term sick leave (using a proportional hazards model). We used a cross-validation approach to counter the risk of significant results due to multiple testing. Out of 1,052 tests, we found 599 significant instances of DIF/DIE, 69 of which showed both practical and statistical significance across two independent samples. Most DIF occurred for job type (in 20 cases), while we found little DIF for age, gender, education, social class and sector. DIE seemed to pertain to particular items, which showed DIE in the same direction for several outcome variables. The results allowed a preliminary identification of items that have a positive impact on construct validity and items that have negative impact on construct validity. These results can be used to develop better shortform measures and to improve the conceptual framework, items and scales of the COPSOQ II. We conclude that tests of DIF and DIE are useful for evaluating construct validity.

Identification of the prediction model for dengue incidence in Can Tho city, a Mekong Delta area in Vietnam.

PubMed

Phung, Dung; Huang, Cunrui; Rutherford, Shannon; Chu, Cordia; Wang, Xiaoming; Nguyen, Minh; Nguyen, Nga Huy; Manh, Cuong Do

2015-01-01

The Mekong Delta is highly vulnerable to climate change and a dengue endemic area in Vietnam. This study aims to examine the association between climate factors and dengue incidence and to identify the best climate prediction model for dengue incidence in Can Tho city, the Mekong Delta area in Vietnam. We used three different regression models comprising: standard multiple regression model (SMR), seasonal autoregressive integrated moving average model (SARIMA), and Poisson distributed lag model (PDLM) to examine the association between climate factors and dengue incidence over the period 2003-2010. We validated the models by forecasting dengue cases for the period of January-December, 2011 using the mean absolute percentage error (MAPE). Receiver operating characteristics curves were used to analyze the sensitivity of the forecast of a dengue outbreak. The results indicate that temperature and relative humidity are significantly associated with changes in dengue incidence consistently across the model methods used, but not cumulative rainfall. The Poisson distributed lag model (PDLM) performs the best prediction of dengue incidence for a 6, 9, and 12-month period and diagnosis of an outbreak however the SARIMA model performs a better prediction of dengue incidence for a 3-month period. The simple or standard multiple regression performed highly imprecise prediction of dengue incidence. We recommend a follow-up study to validate the model on a larger scale in the Mekong Delta region and to analyze the possibility of incorporating a climate-based dengue early warning method into the national dengue surveillance system. Copyright © 2014 Elsevier B.V. All rights reserved.

Deadlines at work and sleep quality. Cross-sectional and longitudinal findings among Danish knowledge workers.

PubMed

Rugulies, Reiner; Martin, Marie H T; Garde, Anne Helene; Persson, Roger; Albertsen, Karen

2012-03-01

Exposure to deadlines at work is increasing in several countries and may affect health. We aimed to investigate cross-sectional and longitudinal associations between frequency of difficult deadlines at work and sleep quality. Study participants were knowledge workers, drawn from a representative sample of Danish employees who responded to a baseline questionnaire in 2006 (n = 363) and a follow-up questionnaire in 2007 (n = 302). Frequency of difficult deadlines was measured by self-report and categorized into low, intermediate, and high. Sleep quality was measured with a Total Sleep Quality Score and two indexes (Awakening Index and Disturbed Sleep Index) derived from the Karolinska Sleep Questionnaire. Analyses on the association between frequency of deadlines and sleep quality scores were conducted with multiple linear regression models, adjusted for potential confounders. In addition, we used multiple logistic regression models to analyze whether frequency of deadlines at baseline predicted caseness of sleep problems at follow-up among participants free of sleep problems at baseline. Frequent deadlines were cross-sectionally and longitudinally associated with poorer sleep quality on all three sleep quality measures. Associations in the longitudinal analyses were greatly attenuated when we adjusted for baseline sleep quality. The logistic regression analyses showed that frequent deadlines at baseline were associated with elevated odds ratios for caseness of sleep problems at follow-up, however, confidence intervals were wide in these analyses. Frequent deadlines at work were associated with poorer sleep quality among Danish knowledge workers. We recommend investigating the relation between deadlines and health endpoints in large-scale epidemiologic studies. Copyright © 2011 Wiley Periodicals, Inc.

Use of Thematic Mapper for water quality assessment

NASA Technical Reports Server (NTRS)

Horn, E. M.; Morrissey, L. A.

1984-01-01

The evaluation of simulated TM data obtained on an ER-2 aircraft at twenty-five predesignated sample sites for mapping water quality factors such as conductivity, pH, suspended solids, turbidity, temperature, and depth, is discussed. Using a multiple regression for the seven TM bands, an equation is developed for the suspended solids. TM bands 1, 2, 3, 4, and 6 are used with logarithm conductivity in a multiple regression. The assessment of regression equations for a high coefficient of determination (R-squared) and statistical significance is considered. Confidence intervals about the mean regression point are calculated in order to assess the robustness of the regressions used for mapping conductivity, turbidity, and suspended solids, and by regressing random subsamples of sites and comparing the resultant range of R-squared, cross validation is conducted.

INTRODUCTION TO A COMBINED MULTIPLE LINEAR REGRESSION AND ARMA MODELING APPROACH FOR BEACH BACTERIA PREDICTION

EPA Science Inventory

Due to the complexity of the processes contributing to beach bacteria concentrations, many researchers rely on statistical modeling, among which multiple linear regression (MLR) modeling is most widely used. Despite its ease of use and interpretation, there may be time dependence...

Determining the Spatial and Seasonal Variability in OM/OC Ratios across the U.S. Using Multiple Regression

EPA Science Inventory

Data from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network are used to estimate organic mass to organic carbon (OM/OC) ratios across the United States by extending previously published multiple regression techniques. Our new methodology addresses com...

Analysis and Interpretation of Findings Using Multiple Regression Techniques

ERIC Educational Resources Information Center

Hoyt, William T.; Leierer, Stephen; Millington, Michael J.

2006-01-01

Multiple regression and correlation (MRC) methods form a flexible family of statistical techniques that can address a wide variety of different types of research questions of interest to rehabilitation professionals. In this article, we review basic concepts and terms, with an emphasis on interpretation of findings relevant to research questions…

Tracking the Gender Pay Gap: A Case Study

ERIC Educational Resources Information Center

Travis, Cheryl B.; Gross, Louis J.; Johnson, Bruce A.

2009-01-01

This article provides a short introduction to standard considerations in the formal study of wages and illustrates the use of multiple regression and resampling simulation approaches in a case study of faculty salaries at one university. Multiple regression is especially beneficial where it provides information on strength of association, specific…

Estimating air drying times of lumber with multiple regression

Treesearch

William T. Simpson

2004-01-01

In this study, the applicability of a multiple regression equation for estimating air drying times of red oak, sugar maple, and ponderosa pine lumber was evaluated. The equation allows prediction of estimated air drying times from historic weather records of temperature and relative humidity at any desired location.

Using Robust Variance Estimation to Combine Multiple Regression Estimates with Meta-Analysis

ERIC Educational Resources Information Center

Williams, Ryan

2013-01-01

The purpose of this study was to explore the use of robust variance estimation for combining commonly specified multiple regression models and for combining sample-dependent focal slope estimates from diversely specified models. The proposed estimator obviates traditionally required information about the covariance structure of the dependent…

Multiple Regression: A Leisurely Primer.

ERIC Educational Resources Information Center

Daniel, Larry G.; Onwuegbuzie, Anthony J.

Multiple regression is a useful statistical technique when the researcher is considering situations in which variables of interest are theorized to be multiply caused. It may also be useful in those situations in which the researchers is interested in studies of predictability of phenomena of interest. This paper provides an introduction to…

Using Monte Carlo Techniques to Demonstrate the Meaning and Implications of Multicollinearity

ERIC Educational Resources Information Center

Vaughan, Timothy S.; Berry, Kelly E.

2005-01-01

This article presents an in-class Monte Carlo demonstration, designed to demonstrate to students the implications of multicollinearity in a multiple regression study. In the demonstration, students already familiar with multiple regression concepts are presented with a scenario in which the "true" relationship between the response and…

Assessing the Impact of Influential Observations on Multiple Regression Analysis on Human Resource Research.

ERIC Educational Resources Information Center

Bates, Reid A.; Holton, Elwood F., III; Burnett, Michael F.

1999-01-01

A case study of learning transfer demonstrates the possible effect of influential observation on linear regression analysis. A diagnostic method that tests for violation of assumptions, multicollinearity, and individual and multiple influential observations helps determine which observation to delete to eliminate bias. (SK)

Population-Based Questionnaire Survey on Health Effects of Aircraft Noise on Residents Living around U.S. Airfields in the RYUKYUS—PART i: AN Analysis of 12 Scale Scores

NASA Astrophysics Data System (ADS)

MIYAKITA, T.; MATSUI, T.; ITO, A.; TOKUYAMA, T.; HIRAMATSU, K.; OSADA, Y.; YAMAMOTO, T.

2002-02-01

A questionnaire survey was made of health effects of aircraft noise on residents living around Kadena and Futenma airfields using the Todai Health Index. Aircraft noise exposure expressed by Ldnranged from under 55 to over 70 in the surveyed area. The number of valid answers was 7095, including 848 among the control group. Twelve scale scores were converted to dichotomous variables based on scale scores of the 90 percentile value or the 10 percentile value in the control group. Multiple logistic regression analysis was done taking 12 scale scores converted into the dependent variable andLdn , age (six levels), sex, occupation (four categories) and the interaction of age and sex as the independent variables. Significant dose-response relationships were found in the scale scores for vague complaints, respiratory, digestive, mental instability, depression and nervousness. The results suggest that the residents living around Kadena and Futenma airfields may suffer both physical and mental effects as a result of exposure to military aircraft noise and that such responses increase with the level of noise exposure (Ldn).

Multiple network-constrained regressions expand insights into influenza vaccination responses.

PubMed

Avey, Stefan; Mohanty, Subhasis; Wilson, Jean; Zapata, Heidi; Joshi, Samit R; Siconolfi, Barbara; Tsang, Sui; Shaw, Albert C; Kleinstein, Steven H

2017-07-15

Systems immunology leverages recent technological advancements that enable broad profiling of the immune system to better understand the response to infection and vaccination, as well as the dysregulation that occurs in disease. An increasingly common approach to gain insights from these large-scale profiling experiments involves the application of statistical learning methods to predict disease states or the immune response to perturbations. However, the goal of many systems studies is not to maximize accuracy, but rather to gain biological insights. The predictors identified using current approaches can be biologically uninterpretable or present only one of many equally predictive models, leading to a narrow understanding of the underlying biology. Here we show that incorporating prior biological knowledge within a logistic modeling framework by using network-level constraints on transcriptional profiling data significantly improves interpretability. Moreover, incorporating different types of biological knowledge produces models that highlight distinct aspects of the underlying biology, while maintaining predictive accuracy. We propose a new framework, Logistic Multiple Network-constrained Regression (LogMiNeR), and apply it to understand the mechanisms underlying differential responses to influenza vaccination. Although standard logistic regression approaches were predictive, they were minimally interpretable. Incorporating prior knowledge using LogMiNeR led to models that were equally predictive yet highly interpretable. In this context, B cell-specific genes and mTOR signaling were associated with an effective vaccination response in young adults. Overall, our results demonstrate a new paradigm for analyzing high-dimensional immune profiling data in which multiple networks encoding prior knowledge are incorporated to improve model interpretability. The R source code described in this article is publicly available at https://bitbucket.org/kleinstein/logminer . steven.kleinstein@yale.edu or stefan.avey@yale.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Multi-Scale, Direct and Indirect Effects of the Urban Stream Syndrome on Amphibian Communities in Streams

PubMed Central

Canessa, Stefano; Parris, Kirsten M.

2013-01-01

Urbanization affects streams by modifying hydrology, increasing pollution and disrupting in-stream and riparian conditions, leading to negative responses by biotic communities. Given the global trend of increasing urbanization, improved understanding of its direct and indirect effects at multiple scales is needed to assist management. The theory of stream ecology suggests that the riverscape and the surrounding landscape are inextricably linked, and watershed-scale processes will also affect in-stream conditions and communities. This is particularly true for species with semi-aquatic life cycles, such as amphibians, which transfer energy between streams and surrounding terrestrial areas. We related measures of urbanization at different scales to frog communities in streams along an urbanization gradient in Melbourne, Australia. We used boosted regression trees to determine the importance of predictors and the shape of species responses. We then used structural equation models to investigate possible indirect effects of watershed imperviousness on in-stream parameters. The proportion of riparian vegetation and road density surrounding the site at the reach scale (500-m radius) had positive and negative effects, respectively, on species richness and on the occurrence of the two most common species in the area ( Crinia signifera and Limnodynastesdumerilii ). Road density and local aquatic vegetation interacted in influencing species richness, suggesting that isolation of a site can prevent colonization, in spite of apparently good local habitat. Attenuated imperviousness at the catchment scale had a negative effect on local aquatic vegetation, indicating possible indirect effects on frog species not revealed by single-level models. Processes at the landscape scale, particularly related to individual ranging distances, can affect frog species directly and indirectly. Catchment imperviousness might not affect adult frogs directly, but by modifying hydrology it can disrupt local vegetation and prove indirectly detrimental. Integrating multiple-scale management actions may help to meet conservation targets for streams in the face of urbanization. PMID:23922963

Hierarchical faunal filters: An approach to assessing effects of habitat and nonnative species on native fishes

USGS Publications Warehouse

Quist, M.C.; Rahel, F.J.; Hubert, W.A.

2005-01-01

Understanding factors related to the occurrence of species across multiple spatial and temporal scales is critical to the conservation and management of native fishes, especially for those species at the edge of their natural distribution. We used the concept of hierarchical faunal filters to provide a framework for investigating the influence of habitat characteristics and normative piscivores on the occurrence of 10 native fishes in streams of the North Platte River watershed in Wyoming. Three faunal filters were developed for each species: (i) large-scale biogeographic, (ii) local abiotic, and (iii) biotic. The large-scale biogeographic filter, composed of elevation and stream-size thresholds, was used to determine the boundaries within which each species might be expected to occur. Then, a local abiotic filter (i.e., habitat associations), developed using binary logistic-regression analysis, estimated the probability of occurrence of each species from features such as maximum depth, substrate composition, submergent aquatic vegetation, woody debris, and channel morphology (e.g., amount of pool habitat). Lastly, a biotic faunal filter was developed using binary logistic regression to estimate the probability of occurrence of each species relative to the abundance of nonnative piscivores in a reach. Conceptualising fish assemblages within a framework of hierarchical faunal filters is simple and logical, helps direct conservation and management activities, and provides important information on the ecology of fishes in the western Great Plains of North America. ?? Blackwell Munksgaard, 2004.

Estimating the impact of mineral aerosols on crop yields in food insecure regions using statistical crop models

NASA Astrophysics Data System (ADS)

Hoffman, A.; Forest, C. E.; Kemanian, A.

2016-12-01

A significant number of food-insecure nations exist in regions of the world where dust plays a large role in the climate system. While the impacts of common climate variables (e.g. temperature, precipitation, ozone, and carbon dioxide) on crop yields are relatively well understood, the impact of mineral aerosols on yields have not yet been thoroughly investigated. This research aims to develop the data and tools to progress our understanding of mineral aerosol impacts on crop yields. Suspended dust affects crop yields by altering the amount and type of radiation reaching the plant, modifying local temperature and precipitation. While dust events (i.e. dust storms) affect crop yields by depleting the soil of nutrients or by defoliation via particle abrasion. The impact of dust on yields is modeled statistically because we are uncertain which impacts will dominate the response on national and regional scales considered in this study. Multiple linear regression is used in a number of large-scale statistical crop modeling studies to estimate yield responses to various climate variables. In alignment with previous work, we develop linear crop models, but build upon this simple method of regression with machine-learning techniques (e.g. random forests) to identify important statistical predictors and isolate how dust affects yields on the scales of interest. To perform this analysis, we develop a crop-climate dataset for maize, soybean, groundnut, sorghum, rice, and wheat for the regions of West Africa, East Africa, South Africa, and the Sahel. Random forest regression models consistently model historic crop yields better than the linear models. In several instances, the random forest models accurately capture the temperature and precipitation threshold behavior in crops. Additionally, improving agricultural technology has caused a well-documented positive trend that dominates time series of global and regional yields. This trend is often removed before regression with traditional crop models, but likely at the cost of removing climate information. Our random forest models consistently discover the positive trend without removing any additional data. The application of random forests as a statistical crop model provides insight into understanding the impact of dust on yields in marginal food producing regions.

High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models

PubMed Central

Welp, Gerhard; Thiel, Michael

2017-01-01

Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat), terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties–sand, silt, clay, cation exchange capacity (CEC), soil organic carbon (SOC) and nitrogen–in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models–multiple linear regression (MLR), random forest regression (RFR), support vector machine (SVM), stochastic gradient boosting (SGB)–were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June) were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices of redness, coloration and saturation were prominent predictors in digital soil mapping. Considering the increased availability of freely available Remote Sensing data (e.g. Landsat, SRTM, Sentinels), soil information at local and regional scales in data poor regions such as West Africa can be improved with relatively little financial and human resources. PMID:28114334

High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models.

PubMed

Forkuor, Gerald; Hounkpatin, Ozias K L; Welp, Gerhard; Thiel, Michael

2017-01-01

Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effective and less time consuming compared to traditional soil mapping approaches. But the potentials of Remote Sensing data in improving knowledge of local scale soil information in West Africa have not been fully explored. This study investigated the use of high spatial resolution satellite data (RapidEye and Landsat), terrain/climatic data and laboratory analysed soil samples to map the spatial distribution of six soil properties-sand, silt, clay, cation exchange capacity (CEC), soil organic carbon (SOC) and nitrogen-in a 580 km2 agricultural watershed in south-western Burkina Faso. Four statistical prediction models-multiple linear regression (MLR), random forest regression (RFR), support vector machine (SVM), stochastic gradient boosting (SGB)-were tested and compared. Internal validation was conducted by cross validation while the predictions were validated against an independent set of soil samples considering the modelling area and an extrapolation area. Model performance statistics revealed that the machine learning techniques performed marginally better than the MLR, with the RFR providing in most cases the highest accuracy. The inability of MLR to handle non-linear relationships between dependent and independent variables was found to be a limitation in accurately predicting soil properties at unsampled locations. Satellite data acquired during ploughing or early crop development stages (e.g. May, June) were found to be the most important spectral predictors while elevation, temperature and precipitation came up as prominent terrain/climatic variables in predicting soil properties. The results further showed that shortwave infrared and near infrared channels of Landsat8 as well as soil specific indices of redness, coloration and saturation were prominent predictors in digital soil mapping. Considering the increased availability of freely available Remote Sensing data (e.g. Landsat, SRTM, Sentinels), soil information at local and regional scales in data poor regions such as West Africa can be improved with relatively little financial and human resources.

A multimodel approach to interannual and seasonal prediction of Danube discharge anomalies

NASA Astrophysics Data System (ADS)

Rimbu, Norel; Ionita, Monica; Patrut, Simona; Dima, Mihai

2010-05-01

Interannual and seasonal predictability of Danube river discharge is investigated using three model types: 1) time series models 2) linear regression models of discharge with large-scale climate mode indices and 3) models based on stable teleconnections. All models are calibrated using discharge and climatic data for the period 1901-1977 and validated for the period 1978-2008 . Various time series models, like autoregressive (AR), moving average (MA), autoregressive and moving average (ARMA) or singular spectrum analysis and autoregressive moving average (SSA+ARMA) models have been calibrated and their skills evaluated. The best results were obtained using SSA+ARMA models. SSA+ARMA models proved to have the highest forecast skill also for other European rivers (Gamiz-Fortis et al. 2008). Multiple linear regression models using large-scale climatic mode indices as predictors have a higher forecast skill than the time series models. The best predictors for Danube discharge are the North Atlantic Oscillation (NAO) and the East Atlantic/Western Russia patterns during winter and spring. Other patterns, like Polar/Eurasian or Tropical Northern Hemisphere (TNH) are good predictors for summer and autumn discharge. Based on stable teleconnection approach (Ionita et al. 2008) we construct prediction models through a combination of sea surface temperature (SST), temperature (T) and precipitation (PP) from the regions where discharge and SST, T and PP variations are stable correlated. Forecast skills of these models are higher than forecast skills of the time series and multiple regression models. The models calibrated and validated in our study can be used for operational prediction of interannual and seasonal Danube discharge anomalies. References Gamiz-Fortis, S., D. Pozo-Vazquez, R.M. Trigo, and Y. Castro-Diez, Quantifying the predictability of winter river flow in Iberia. Part I: intearannual predictability. J. Climate, 2484-2501, 2008. Gamiz-Fortis, S., D. Pozo-Vazquez, R.M. Trigo, and Y. Castro-Diez, Quantifying the predictability of winter river flow in Iberia. Part II: seasonal predictability. J. Climate, 2503-2518, 2008. Ionita, M., G. Lohmann, and N. Rimbu, Prediction of spring Elbe river discharge based on stable teleconnections with global temperature and precipitation. J. Climate. 6215-6226, 2008.

Psychosocial risks associated with multiple births resulting from assisted reproduction: a Spanish sample.

PubMed

Roca de Bes, Montserrat; Gutierrez Maldonado, José; Gris Martínez, José M

2009-09-01

To determine the psychosocial risks associated with multiple births (twins or triplets) resulting from assisted reproductive technology (ART). Transverse study. Infertility units of a university hospital and a private hospital. Mothers and fathers of children between 6 months and 4 years conceived by ART (n = 123). The sample was divided into three groups: parents of singletons (n = 77), twins (n = 37), and triplets (n = 9). The questionnaire was self-administered by patients. It was either completed at the hospital or mailed to participants' homes. Scales measured material needs, quality of life, social stigma, depression, stress, and marital satisfaction. Logistic regression models were applied. Significant odds ratios were obtained for the number of children, material needs, social stigma, quality of life, and marital satisfaction. The results were more significant for data provided by mothers than by fathers. The informed consent form handed out at the beginning of ART should include information on the high risk of conceiving twins and triplets and on the possible psychosocial consequences of multiple births. As soon as a multiple pregnancy is confirmed, it would be useful to provide information on support groups and institutions. Psychological advice should also be given to the parents.

Self-reported quality of life in multiple sclerosis patients: preliminary results based on the Polish MS Registry.

PubMed

Brola, Waldemar; Sobolewski, Piotr; Fudala, Małgorzata; Flaga, Stanisław; Jantarski, Konrad; Ryglewicz, Danuta; Potemkowski, Andrzej

2016-01-01

The aim of the study was to analyze selected clinical and sociodemographic factors and their effects on the quality of life (QoL) of multiple sclerosis (MS) patients registered in the Polish MS Registry. This was a cross-sectional observational study performed in Poland. Data on personal and disease-specific factors were collected between January 1, 2011, and December 31, 2015, via the web portal of the Polish MS Registry. All patients were assessed by a physician and asked to complete the Polish language versions of the following self-evaluation questionnaires: EuroQol 5-Dimensions, EuroQoL Visual Analog Scale, and Multiple Sclerosis Impact Scale. Univariate analysis and logistic regression were performed to determine the factors associated with QoL. The study included 2,385 patients (female/male ratio 2.3:1) with clinically confirmed MS (mean age 37.8±9.2 years). Average EuroQol 5-Dimensions index was 0.72±0.24, and the mean EuroQoL Visual Analog Scale score was 64.2±22.8. The average Multiple Sclerosis Impact Scale score was 84.6±11.2 (62.2±18.4 for physical condition and 23.8±7.2 for mental condition). Lower QoL scores were significantly associated with higher level of disability (odds ratio [OR], 0.932; 95% confidence interval [CI], 0.876-0.984; P=0.001), age >40 years (OR, 1.042; 95% CI, 0.924-1.158; P=0.012), longer disease duration (OR, 0.482; 95% CI, 0.224-0.998; P=0.042), and lack of disease modifying therapies (OR, 0.024; 95% CI, 0.160-0.835; P=0.024). No significant associations were found between QoL, sex, type of MS course, patient's education, and marital status. The Polish MS Registry is the first national registry for long-term observation that allows for self-evaluation of the QoL. QoL of Polish patients with MS is significantly lower compared with the rest of the population. The parameter is mainly affected by the level of disability, duration of the disease, and limited access to immunomodulatory therapy.

Blending Multiple Nitrogen Dioxide Data Sources for Neighborhood Estimates of Long-Term Exposure for Health Research.

PubMed

Hanigan, Ivan C; Williamson, Grant J; Knibbs, Luke D; Horsley, Joshua; Rolfe, Margaret I; Cope, Martin; Barnett, Adrian G; Cowie, Christine T; Heyworth, Jane S; Serre, Marc L; Jalaludin, Bin; Morgan, Geoffrey G

2017-11-07

Exposure to traffic related nitrogen dioxide (NO 2 ) air pollution is associated with adverse health outcomes. Average pollutant concentrations for fixed monitoring sites are often used to estimate exposures for health studies, however these can be imprecise due to difficulty and cost of spatial modeling at the resolution of neighborhoods (e.g., a scale of tens of meters) rather than at a coarse scale (around several kilometers). The objective of this study was to derive improved estimates of neighborhood NO 2 concentrations by blending measurements with modeled predictions in Sydney, Australia (a low pollution environment). We implemented the Bayesian maximum entropy approach to blend data with uncertainty defined using informative priors. We compiled NO 2 data from fixed-site monitors, chemical transport models, and satellite-based land use regression models to estimate neighborhood annual average NO 2 . The spatial model produced a posterior probability density function of estimated annual average concentrations that spanned an order of magnitude from 3 to 35 ppb. Validation using independent data showed improvement, with root mean squared error improvement of 6% compared with the land use regression model and 16% over the chemical transport model. These estimates will be used in studies of health effects and should minimize misclassification bias.

Broad-scale adaptive genetic variation in alpine plants is driven by temperature and precipitation

PubMed Central

MANEL, STÉPHANIE; GUGERLI, FELIX; THUILLER, WILFRIED; ALVAREZ, NADIR; LEGENDRE, PIERRE; HOLDEREGGER, ROLF; GIELLY, LUDOVIC; TABERLET, PIERRE

2014-01-01

Identifying adaptive genetic variation is a challenging task, in particular in non-model species for which genomic information is still limited or absent. Here, we studied distribution patterns of amplified fragment length polymorphisms (AFLPs) in response to environmental variation, in 13 alpine plant species consistently sampled across the entire European Alps. Multiple linear regressions were performed between AFLP allele frequencies per site as dependent variables and two categories of independent variables, namely Moran’s eigenvector map MEM variables (to account for spatial and unaccounted environmental variation, and historical demographic processes) and environmental variables. These associations allowed the identification of 153 loci of ecological relevance. Univariate regressions between allele frequency and each environmental factor further showed that loci of ecological relevance were mainly correlated with MEM variables. We found that precipitation and temperature were the best environmental predictors, whereas topographic factors were rarely involved in environmental associations. Climatic factors, subject to rapid variation as a result of the current global warming, are known to strongly influence the fate of alpine plants. Our study shows, for the first time for a large number of species, that the same environmental variables are drivers of plant adaptation at the scale of a whole biome, here the European Alps. PMID:22680783

Seagrass meadows (Posidonia oceanica) distribution and trajectories of change

PubMed Central

Telesca, Luca; Belluscio, Andrea; Criscoli, Alessandro; Ardizzone, Giandomenico; Apostolaki, Eugenia T.; Fraschetti, Simonetta; Gristina, Michele; Knittweis, Leyla; Martin, Corinne S.; Pergent, Gérard; Alagna, Adriana; Badalamenti, Fabio; Garofalo, Germana; Gerakaris, Vasilis; Louise Pace, Marie; Pergent-Martini, Christine; Salomidi, Maria

2015-01-01

Posidonia oceanica meadows are declining at alarming rates due to climate change and human activities. Although P. oceanica is considered the most important and well-studied seagrass species of the Mediterranean Sea, to date there has been a limited effort to combine all the spatial information available and provide a complete distribution of meadows across the basin. The aim of this work is to provide a fine-scale assessment of (i) the current and historical known distribution of P. oceanica, (ii) the total area of meadows and (iii) the magnitude of regressive phenomena in the last decades. The outcomes showed the current spatial distribution of P. oceanica, covering a known area of 1,224,707 ha, and highlighted the lack of relevant data in part of the basin (21,471 linear km of coastline). The estimated regression of meadows amounted to 34% in the last 50 years, showing that this generalised phenomenon had to be mainly ascribed to cumulative effects of multiple local stressors. Our results highlighted the importance of enforcing surveys to assess the status and prioritize areas where cost-effective schemes for threats reduction, capable of reversing present patterns of change and ensuring P. oceanica persistence at Mediterranean scale, could be implemented. PMID:26216526

Exploring the Assessment of the DSM-5 Alternative Model for Personality Disorders With the Personality Assessment Inventory.

PubMed

Busch, Alexander J; Morey, Leslie C; Hopwood, Christopher J

2017-01-01

Section III of the Diagnostic and Statistical Manual of Mental Disorders (5th ed. [DSM-5]; American Psychiatric Association, 2013) contains an alternative model for the diagnosis of personality disorder involving the assessment of 25 traits and a global level of overall personality functioning. There is hope that this model will be increasingly used in clinical and research settings, and the ability to apply established instruments to assess these concepts could facilitate this process. This study sought to develop scoring algorithms for these alternative model concepts using scales from the Personality Assessment Inventory (PAI). A multiple regression strategy used to predict scores in 2 undergraduate samples on DSM-5 alternative model instruments: the Personality Inventory for the DSM-5 (PID-5) and the General Personality Pathology scale (GPP; Morey et al., 2011 ). These regression functions resulted in scores that demonstrated promising convergent and discriminant validity across the alternative model concepts, as well as a factor structure in a cross-validation sample that was congruent with the putative structure of the alternative model traits. Results were linked to the PAI community normative data to provide normative information regarding these alternative model concepts that can be used to identify elevated traits and personality functioning level scores.

Psychological dependence on antidepressants in patients with panic disorder: a cross-sectional study.

PubMed

Fujii, Kazuhito; Suzuki, Takefumi; Mimura, Masaru; Uchida, Hiroyuki

2017-01-01

No study has investigated psychological dependence on antidepressants in patients with panic disorder, which was addressed in this study. This study was carried out in four psychiatric clinics in Tokyo, Japan. Individuals were eligible if they were outpatients aged 18 years or older and fulfilled the diagnostic criteria for panic disorder (ICD-10). Assessments included the Japanese Versions of the Severity of Dependence Scale (SDS), the Self-Report Version of Panic Disorder Severity Scale (PDSS-SR), and the Quick Inventory of Depressive Symptomatology-Self Report. Eighty-four individuals were included; of these, 30 patients (35.7%) showed psychological dependence on antidepressants (i.e. a total score of ≥5 in the SDS). A multiple regression analysis showed that PDSS scores and illness duration were correlated positively with SDS total scores. A binary regression model showed that absence of remission (i.e. a total score of ≥5 in the PDSS) and longer duration of illness increased the risk of dependence on antidepressants. Approximately one-third of the patients with panic disorder, receiving antidepressants, fulfilled the criteria for psychological dependence on these drugs. The results underscore the need for close monitoring, especially for those who present severe symptomatology or have a chronic course of the illness.

Development and Psychometric Evaluation of the HPV Clinical Trial Survey for Parents (CTSP-HPV) Using Traditional Survey Development Methods and Community Engagement Principles.

PubMed

Cunningham, Jennifer; Wallston, Kenneth A; Wilkins, Consuelo H; Hull, Pamela C; Miller, Stephania T

2015-12-01

This study describes the development and psychometric evaluation of HPV Clinical Trial Survey for Parents with Children Aged 9 to 15 (CTSP-HPV) using traditional instrument development methods and community engagement principles. An expert panel and parental input informed survey content and parents recommended study design changes (e.g., flyer wording). A convenience sample of 256 parents completed the final survey measuring parental willingness to consent to HPV clinical trial (CT) participation and other factors hypothesized to influence willingness (e.g., HPV vaccine benefits). Cronbach's a, Spearman correlations, and multiple linear regression were used to estimate internal consistency, convergent and discriminant validity, and predictively validity, respectively. Internal reliability was confirmed for all scales (a ≥ 0.70.). Parental willingness was positively associated (p < 0.05) with trust in medical researchers, adolescent CT knowledge, HPV vaccine benefits, advantages of adolescent CTs (r range 0.33-0.42), supporting convergent validity. Moderate discriminant construct validity was also demonstrated. Regression results indicate reasonable predictive validity with the six scales accounting for 31% of the variance in parents' willingness. This instrument can inform interventions based on factors that influence parental willingness, which may lead to the eventual increase in trial participation. Further psychometric testing is warranted. © 2015 Wiley Periodicals, Inc.

Effects of psychological distress on blood pressure in adolescents.

PubMed

Weinrich, S; Weinrich, M; Hardin, S; Gleaton, J; Pesut, D J; Garrison, C

2000-10-01

This cross-sectional survey measured relationships among blood pressure and measures of psychologic distress, family structure, and economic status in a sample of adolescents exposed to Hurricane Hugo. Spielberger's Anger Scale and Derogatis' Brief Symptom Inventory were used. Data analysis revealed 5% of the 1079 adolescents were hypertensive. Multiple regression analyses revealed the following predictors of higher diastolic blood pressure: African-American race, recipient of subsidized lunch, exposure to Hurricane Hugo, and higher anger-in scores in males. The effects of a catastrophic event such as a hurricane on blood pressure and the effects of introjected anger have implications for both health care consumers and providers.

Organizational Commitment and Nurses' Characteristics as Predictors of Job Involvement.

PubMed

Alammar, Kamila; Alamrani, Mashael; Alqahtani, Sara; Ahmad, Muayyad

2016-01-01

To predict nurses' job involvement on the basis of their organizational commitment and personal characteristics at a large tertiary hospital in Saudi Arabia. Data were collected in 2015 from a convenience sample of 558 nurses working at a large tertiary hospital in Riyadh, Saudi Arabia. A cross-sectional correlational design was used in this study. Data were collected using a structured questionnaire. All commitment scales had significant relationships. Multiple linear regression analysis revealed that the model predicted a sizeable proportion of variance in nurses' job involvement (p < 0.001). High organizational commitment enhances job involvement, which may lead to more organizational stability and effectiveness.

A novel simple QSAR model for the prediction of anti-HIV activity using multiple linear regression analysis.

PubMed

Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Markopoulos, John; Igglessi-Markopoulou, Olga

2006-08-01

A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (R (2) (CV) = 0.8160; S (PRESS) = 0.5680) proved to be very accurate both in training and predictive stages.

Deriving percentage study weights in multi-parameter meta-analysis models: with application to meta-regression, network meta-analysis and one-stage individual participant data models.

PubMed

Riley, Richard D; Ensor, Joie; Jackson, Dan; Burke, Danielle L

2017-01-01

Many meta-analysis models contain multiple parameters, for example due to multiple outcomes, multiple treatments or multiple regression coefficients. In particular, meta-regression models may contain multiple study-level covariates, and one-stage individual participant data meta-analysis models may contain multiple patient-level covariates and interactions. Here, we propose how to derive percentage study weights for such situations, in order to reveal the (otherwise hidden) contribution of each study toward the parameter estimates of interest. We assume that studies are independent, and utilise a decomposition of Fisher's information matrix to decompose the total variance matrix of parameter estimates into study-specific contributions, from which percentage weights are derived. This approach generalises how percentage weights are calculated in a traditional, single parameter meta-analysis model. Application is made to one- and two-stage individual participant data meta-analyses, meta-regression and network (multivariate) meta-analysis of multiple treatments. These reveal percentage study weights toward clinically important estimates, such as summary treatment effects and treatment-covariate interactions, and are especially useful when some studies are potential outliers or at high risk of bias. We also derive percentage study weights toward methodologically interesting measures, such as the magnitude of ecological bias (difference between within-study and across-study associations) and the amount of inconsistency (difference between direct and indirect evidence in a network meta-analysis).

Clinical Importance of Steps Taken per Day among Persons with Multiple Sclerosis

PubMed Central

Motl, Robert W.; Pilutti, Lara A.; Learmonth, Yvonne C.; Goldman, Myla D.; Brown, Ted

2013-01-01

Background The number of steps taken per day (steps/day) provides a reliable and valid outcome of free-living walking behavior in persons with multiple sclerosis (MS). Objective This study examined the clinical meaningfulness of steps/day using the minimal clinically important difference (MCID) value across stages representing the developing impact of MS. Methods This study was a secondary analysis of de-identified data from 15 investigations totaling 786 persons with MS and 157 healthy controls. All participants provided demographic information and wore an accelerometer or pedometer during the waking hours of a 7-day period. Those with MS further provided real-life, health, and clinical information and completed the Multiple Sclerosis Walking Scale-12 (MSWS-12) and Patient Determined Disease Steps (PDDS) scale. MCID estimates were based on regression analyses and analysis of variance for between group differences. Results The mean MCID from self-report scales that capture subtle changes in ambulation (1-point change in PDSS scores and 10-point change in MSWS-12 scores) was 779 steps/day (14% of mean score for MS sample); the mean MCID for clinical/health outcomes (MS type, duration, weight status) was 1,455 steps/day (26% of mean score for MS sample); real-life anchors (unemployment, divorce, assistive device use) resulted in a mean MCID of 2,580 steps/day (45% of mean score for MS sample); and the MCID for the cumulative impact of MS (MS vs. control) was 2,747 steps/day (48% of mean score for MS sample). Conclusion The change in motion sensor output of ∼800 steps/day appears to represent a lower-bound estimate of clinically meaningful change in free-living walking behavior in interventions of MS. PMID:24023843

Relationship between pain and post-traumatic stress symptoms in palliative care.

PubMed

Roth, Maya L; St Cyr, Kate; Harle, Ingrid; Katz, Joel D

2013-08-01

Previous research suggests that patients receiving palliative care may simultaneously experience poorly managed pain and post-traumatic stress disorder (PTSD)-related symptoms as a result of their deteriorating health. To: 1) examine predictors of PTSD-related symptoms in patients requiring palliative care; 2) assess whether anxiety, depression, pain catastrophizing, and pain anxiety mediate the relationship between pain interference and PTSD-related symptoms; and 3) evaluate the impact of these variables on pain interference and PTSD-related symptoms. One hundred patients receiving palliative care at one of two palliative care sites in London, ON, Canada, completed the PTSD Checklist-Civilian version (PCL-C), the Hospital Anxiety and Depression Scale (HADS), the Pain Catastrophizing Scale (PCS), the Brief Pain Inventory-Short Form (BPI-SF), and the Pain Anxiety Symptoms Scale-20 (PASS-20). Hierarchical multiple regressions were used to examine HADS-Anxiety, HADS-Depression, PCS and PASS-20 scores as predictors of PCL-C scores; and mediation analyses were used to test the effect of HADS-Anxiety, HADS-Depression, PCS, and PASS-20 on the relationship between BPI-SF interference and PCL-C. Mediators that significantly affected this relationship in the individual mediator models were entered into a multiple mediator model. Only pain anxiety and pain catastrophizing emerged as significant mediators of the relationship between pain interference and PTSD-related symptoms. After being entered in a multiple mediator model, pain anxiety emerged as the strongest mediator. The findings of the present study reveal that pain and PTSD-related symptoms are important concerns in palliative care, and that pain must be addressed to best meet the needs of this population. Copyright © 2013 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.

The association between sexual satisfaction and body image in women.

PubMed

Pujols, Yasisca; Seal, Brooke N; Meston, Cindy M

2010-02-01

Although sexual functioning has been linked to sexual satisfaction, it only partially explains the degree to which women report being sexually satisfied. Other factors include quality of life, relational variables, and individual factors such as body image. Of the few studies that have investigated the link between body image and sexual satisfaction, most have considered body image to be a single construct and have shown mixed results. The present study assessed multiple body image variables in order to better understand which aspects of body image influence multiple domains of sexual satisfaction, including sexual communication, compatibility, contentment, personal concern, and relational concern in a community sample of women. Women between the ages of 18 and 49 years in sexual relationships (N = 154) participated in an Internet survey that assessed sexual functioning, five domains of sexual satisfaction, and several body image variables. Body image variables included the sexual attractiveness, weight concern, and physical condition subscales of the Body Esteem Scale, the appearance-based subscale of the Cognitive Distractions During Sexual Activity Scale, and body mass index. Total score of the Sexual Satisfaction Scale for Women was the main outcome measure. Sexual functioning was measured by a modified Female Sexual Function Index. Consistent with expectations, correlations indicated significant positive relationships between sexual functioning, sexual satisfaction, and all body image variables. A multiple regression analysis revealed that sexual satisfaction was predicted by high body esteem and low frequency of appearance-based distracting thoughts during sexual activity, even after controlling for sexual functioning status. Several aspects of body image, including weight concern, physical condition, sexual attractiveness, and thoughts about the body during sexual activity predict sexual satisfaction in women. The findings suggest that women who experience low sexual satisfaction may benefit from treatments that target these specific aspects of body image.

Power spectrum scale invariance as a neural marker of cocaine misuse and altered cognitive control.

PubMed

Ide, Jaime S; Hu, Sien; Zhang, Sheng; Mujica-Parodi, Lilianne R; Li, Chiang-Shan R

2016-01-01

Magnetic resonance imaging (MRI) has highlighted the effects of chronic cocaine exposure on cerebral structures and functions, and implicated the prefrontal cortices in deficits of cognitive control. Recent investigations suggest power spectrum scale invariance (PSSI) of cerebral blood oxygenation level dependent (BOLD) signals as a neural marker of cerebral activity. We examined here how PSSI is altered in association with cocaine misuse and impaired cognitive control. Eighty-eight healthy (HC) and seventy-five age and gender matched cocaine dependent (CD) adults participated in functional MRI of a stop signal task (SST). BOLD images were preprocessed using standard procedures in SPM, including detrending, band-pass filtering (0.01-0.25 Hz), and correction for head motions. Voxel-wise PSSI measures were estimated by a linear fit of the power spectrum with a log-log scale. In group analyses, we examined differences in PSSI between HC and CD, and its association with clinical and behavioral variables using a multiple regression. A critical component of cognitive control is post-signal behavioral adjustment, which is compromised in cocaine dependence. Therefore, we examined the PSSI changes in association with post-signal slowing (PSS) in the SST. Compared to HC, CD showed decreased PSS and PSSI in multiple frontoparietal regions. PSSI was positively correlated with PSS in HC in multiple regions, including the left inferior frontal gyrus (IFG) and right supramarginal gyrus (SMG), which showed reduced PSSI in CD. These findings suggest disrupted connectivity dynamics in the fronto-parietal areas in association with post-signal behavioral adjustment in cocaine addicts. These new findings support PSSI as a neural marker of impaired cognitive control in cocaine addiction.

Sexual function in young women with type 1 diabetes: the METRO study.

PubMed

Maiorino, M I; Bellastella, G; Castaldo, F; Petrizzo, M; Giugliano, D; Esposito, K

2017-02-01

The aim of this study was to evaluate the prevalence and risk factors associated with female sexual dysfunction (FSD) in young women with type 1 diabetes treated with different intensive insulin regimens. Type 1 diabetic women aged 18-35 years were included in this study if they had stable couple relationship and no oral contraceptive use. All women were asked to complete the Female Sexual Function Index (FSFI) and other validated multiple-choice questionnaires assessing sexual-related distress (Female Sexual Distress Scale, FSDS), quality of life (SF-36 Health Survey), physical activity (International Physical Activity Questionnaire), depressive symptoms (Zung Self-Rating Depression Scale, SRDS) and diabetes-related problems (Diabetes Integration Scale ATT-19). FSD was diagnosed according to a FSFI score higher than 26.55 and a FSDS score lower than 15. The overall prevalence of FSD in diabetic and control women was 20 and 15 %, respectively (P = 0.446). Compared with the continuous subcutaneous insulin infusion group and control women, diabetic women on multiple daily injections (MDI) had lower global FSFI score (P = 0.007), FSDS score (P = 0.045) and domains such as arousal (P = 0.006), lubrication and satisfaction scores (P < 0.001 for both). In the multiple regression analysis, only the mental component summary (P = 0.047) and the SRDS score (P = 0.042) were independent predictors of FSFI score in the overall diabetic women. Young women with type 1 diabetes wearing an insulin pump show a prevalence of sexual dysfunction similar to that of healthy age-matched women, but sexual function was significantly impaired in diabetic women on MDI therapy. Depression and the mental health status were independent predictors for FSD in diabetic women.

Preference-based Health status in a German outpatient cohort with multiple sclerosis

PubMed Central

2013-01-01

Background To prospectively determine health status and health utility and its predictors in patients with multiple sclerosis (MS). Methods A total of 144 MS patients (mean age: 41.0 ±11.3y) with different subtypes (patterns of progression) and severities of MS were recruited in an outpatient university clinic in Germany. Patients completed a questionnaire at baseline (n = 144), 6 months (n = 65) and 12 months (n = 55). Health utilities were assessed using the EuroQol instrument (EQ-5D, EQ VAS). Health status was assessed by several scales (Expanded Disability Severity Scale (EDSS), Modified Fatigue Impact Scale (M-FIS), Functional Assessment of MS (FAMS), Beck Depression Inventory (BDI-II) and Multiple Sclerosis Functional Composite (MSFC)). Additionally, demographic and socioeconomic parameters were assessed. Multivariate linear and logistic regressions were applied to reveal independent predictors of health status. Results Health status is substantially diminished in MS patients and the EQ VAS was considerably lower than that of the general German population. No significant change in health-status parameters was observed over a 12-months period. Multivariate analyses revealed M-FIS, BDI-II, MSFC, and EDSS to be significant predictors of reduced health status. Socioeconomic and socio-demographic parameters such as working status, family status, number of household inhabitants, age, and gender did not prove significant in multivariate analyses. Conclusion MS considerably impairs patients’ health status. Guidelines aiming to improve self-reported health status should include treatment options for depression and fatigue. Physicians should be aware of depression and fatigue as co-morbidities. Future studies should consider the minimal clinical difference when health status is a primary outcome. PMID:24089999

National scale biomass estimators for United States tree species

Treesearch

Jennifer C. Jenkins; David C. Chojnacky; Linda S. Heath; Richard A. Birdsey

2003-01-01

Estimates of national-scale forest carbon (C) stocks and fluxes are typically based on allometric regression equations developed using dimensional analysis techniques. However, the literature is inconsistent and incomplete with respect to large-scale forest C estimation. We compiled all available diameter-based allometric regression equations for estimating total...

[Application of SAS macro to evaluated multiplicative and additive interaction in logistic and Cox regression in clinical practices].

PubMed

Nie, Z Q; Ou, Y Q; Zhuang, J; Qu, Y J; Mai, J Z; Chen, J M; Liu, X Q

2016-05-01

Conditional logistic regression analysis and unconditional logistic regression analysis are commonly used in case control study, but Cox proportional hazard model is often used in survival data analysis. Most literature only refer to main effect model, however, generalized linear model differs from general linear model, and the interaction was composed of multiplicative interaction and additive interaction. The former is only statistical significant, but the latter has biological significance. In this paper, macros was written by using SAS 9.4 and the contrast ratio, attributable proportion due to interaction and synergy index were calculated while calculating the items of logistic and Cox regression interactions, and the confidence intervals of Wald, delta and profile likelihood were used to evaluate additive interaction for the reference in big data analysis in clinical epidemiology and in analysis of genetic multiplicative and additive interactions.

Multiple regression for physiological data analysis: the problem of multicollinearity.

PubMed

Slinker, B K; Glantz, S A

1985-07-01

Multiple linear regression, in which several predictor variables are related to a response variable, is a powerful statistical tool for gaining quantitative insight into complex in vivo physiological systems. For these insights to be correct, all predictor variables must be uncorrelated. However, in many physiological experiments the predictor variables cannot be precisely controlled and thus change in parallel (i.e., they are highly correlated). There is a redundancy of information about the response, a situation called multicollinearity, that leads to numerical problems in estimating the parameters in regression equations; the parameters are often of incorrect magnitude or sign or have large standard errors. Although multicollinearity can be avoided with good experimental design, not all interesting physiological questions can be studied without encountering multicollinearity. In these cases various ad hoc procedures have been proposed to mitigate multicollinearity. Although many of these procedures are controversial, they can be helpful in applying multiple linear regression to some physiological problems.

Testing Mediation Using Multiple Regression and Structural Equation Modeling Analyses in Secondary Data

ERIC Educational Resources Information Center

Li, Spencer D.

2011-01-01

Mediation analysis in child and adolescent development research is possible using large secondary data sets. This article provides an overview of two statistical methods commonly used to test mediated effects in secondary analysis: multiple regression and structural equation modeling (SEM). Two empirical studies are presented to illustrate the…

A Simple and Convenient Method of Multiple Linear Regression to Calculate Iodine Molecular Constants

ERIC Educational Resources Information Center

Cooper, Paul D.

2010-01-01

A new procedure using a student-friendly least-squares multiple linear-regression technique utilizing a function within Microsoft Excel is described that enables students to calculate molecular constants from the vibronic spectrum of iodine. This method is advantageous pedagogically as it calculates molecular constants for ground and excited…

Conjoint Analysis: A Study of the Effects of Using Person Variables.

ERIC Educational Resources Information Center

Fraas, John W.; Newman, Isadore

Three statistical techniques--conjoint analysis, a multiple linear regression model, and a multiple linear regression model with a surrogate person variable--were used to estimate the relative importance of five university attributes for students in the process of selecting a college. The five attributes include: availability and variety of…

An Exploratory Study of Face-to-Face and Cyberbullying in Sixth Grade Students

ERIC Educational Resources Information Center

Accordino, Denise B.; Accordino, Michael P.

2011-01-01

In a pilot study, sixth grade students (N = 124) completed a questionnaire assessing students' experience with bullying and cyberbullying, demographic information, quality of parent-child relationship, and ways they have dealt with bullying/cyberbullying in the past. Two multiple regression analyses were conducted. The multiple regression analysis…

The Use of Multiple Regression and Trend Analysis to Understand Enrollment Fluctuations. AIR Forum 1979 Paper.

ERIC Educational Resources Information Center

Campbell, S. Duke; Greenberg, Barry

The development of a predictive equation capable of explaining a significant percentage of enrollment variability at Florida International University is described. A model utilizing trend analysis and a multiple regression approach to enrollment forecasting was adapted to investigate enrollment dynamics at the university. Four independent…

The Use of Multiple Regression Models to Determine if Conjoint Analysis Should Be Conducted on Aggregate Data.

ERIC Educational Resources Information Center

Fraas, John W.; Newman, Isadore

1996-01-01

In a conjoint-analysis consumer-preference study, researchers must determine whether the product factor estimates, which measure consumer preferences, should be calculated and interpreted for each respondent or collectively. Multiple regression models can determine whether to aggregate data by examining factor-respondent interaction effects. This…

Double Cross-Validation in Multiple Regression: A Method of Estimating the Stability of Results.

ERIC Educational Resources Information Center

Rowell, R. Kevin

In multiple regression analysis, where resulting predictive equation effectiveness is subject to shrinkage, it is especially important to evaluate result replicability. Double cross-validation is an empirical method by which an estimate of invariance or stability can be obtained from research data. A procedure for double cross-validation is…

Synoptic and meteorological drivers of extreme ozone concentrations over Europe

NASA Astrophysics Data System (ADS)

Otero, Noelia Felipe; Sillmann, Jana; Schnell, Jordan L.; Rust, Henning W.; Butler, Tim

2016-04-01

The present work assesses the relationship between local and synoptic meteorological conditions and surface ozone concentration over Europe in spring and summer months, during the period 1998-2012 using a new interpolated data set of observed surface ozone concentrations over the European domain. Along with local meteorological conditions, the influence of large-scale atmospheric circulation on surface ozone is addressed through a set of airflow indices computed with a novel implementation of a grid-by-grid weather type classification across Europe. Drivers of surface ozone over the full distribution of maximum daily 8-hour average values are investigated, along with drivers of the extreme high percentiles and exceedances or air quality guideline thresholds. Three different regression techniques are applied: multiple linear regression to assess the drivers of maximum daily ozone, logistic regression to assess the probability of threshold exceedances and quantile regression to estimate the meteorological influence on extreme values, as represented by the 95th percentile. The relative importance of the input parameters (predictors) is assessed by a backward stepwise regression procedure that allows the identification of the most important predictors in each model. Spatial patterns of model performance exhibit distinct variations between regions. The inclusion of the ozone persistence is particularly relevant over Southern Europe. In general, the best model performance is found over Central Europe, where the maximum temperature plays an important role as a driver of maximum daily ozone as well as its extreme values, especially during warmer months.

Improved spatial regression analysis of diffusion tensor imaging for lesion detection during longitudinal progression of multiple sclerosis in individual subjects

NASA Astrophysics Data System (ADS)

Liu, Bilan; Qiu, Xing; Zhu, Tong; Tian, Wei; Hu, Rui; Ekholm, Sven; Schifitto, Giovanni; Zhong, Jianhui

2016-03-01

Subject-specific longitudinal DTI study is vital for investigation of pathological changes of lesions and disease evolution. Spatial Regression Analysis of Diffusion tensor imaging (SPREAD) is a non-parametric permutation-based statistical framework that combines spatial regression and resampling techniques to achieve effective detection of localized longitudinal diffusion changes within the whole brain at individual level without a priori hypotheses. However, boundary blurring and dislocation limit its sensitivity, especially towards detecting lesions of irregular shapes. In the present study, we propose an improved SPREAD (dubbed improved SPREAD, or iSPREAD) method by incorporating a three-dimensional (3D) nonlinear anisotropic diffusion filtering method, which provides edge-preserving image smoothing through a nonlinear scale space approach. The statistical inference based on iSPREAD was evaluated and compared with the original SPREAD method using both simulated and in vivo human brain data. Results demonstrated that the sensitivity and accuracy of the SPREAD method has been improved substantially by adapting nonlinear anisotropic filtering. iSPREAD identifies subject-specific longitudinal changes in the brain with improved sensitivity, accuracy, and enhanced statistical power, especially when the spatial correlation is heterogeneous among neighboring image pixels in DTI.

Detection of crossover time scales in multifractal detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Ge, Erjia; Leung, Yee

2013-04-01

Fractal is employed in this paper as a scale-based method for the identification of the scaling behavior of time series. Many spatial and temporal processes exhibiting complex multi(mono)-scaling behaviors are fractals. One of the important concepts in fractals is crossover time scale(s) that separates distinct regimes having different fractal scaling behaviors. A common method is multifractal detrended fluctuation analysis (MF-DFA). The detection of crossover time scale(s) is, however, relatively subjective since it has been made without rigorous statistical procedures and has generally been determined by eye balling or subjective observation. Crossover time scales such determined may be spurious and problematic. It may not reflect the genuine underlying scaling behavior of a time series. The purpose of this paper is to propose a statistical procedure to model complex fractal scaling behaviors and reliably identify the crossover time scales under MF-DFA. The scaling-identification regression model, grounded on a solid statistical foundation, is first proposed to describe multi-scaling behaviors of fractals. Through the regression analysis and statistical inference, we can (1) identify the crossover time scales that cannot be detected by eye-balling observation, (2) determine the number and locations of the genuine crossover time scales, (3) give confidence intervals for the crossover time scales, and (4) establish the statistically significant regression model depicting the underlying scaling behavior of a time series. To substantive our argument, the regression model is applied to analyze the multi-scaling behaviors of avian-influenza outbreaks, water consumption, daily mean temperature, and rainfall of Hong Kong. Through the proposed model, we can have a deeper understanding of fractals in general and a statistical approach to identify multi-scaling behavior under MF-DFA in particular.

Cross-cultural adaptation and psychometric properties of the Korean Scale for Internet Addiction (K-Scale) in Japanese high school students.

PubMed

Mak, Kwok-Kei; Nam, JeeEun Karin; Kim, Dongil; Aum, Narae; Choi, Jung-Seok; Cheng, Cecilia; Ko, Huei-Chen; Watanabe, Hiroko

2017-03-01

The Korean Scale for Internet Addiction (K-Scale) was developed in Korea for assessing addictive internet behaviors. This study aims to adopt K-Scale and examine its psychometric properties in Japanese adolescents. In 2014, 589 (36.0% boys) high school students (Grade 10-12) from Japan completed a survey, including items of Japanese versions of K-Scale and Smartphone Scale for Smartphone Addiction (S-Scale). Model fit indices of the original four-factor structure, three-factor structure obtained from exploratory factor analysis, and improved two-factor structure of K-Scale were computed using confirmatory factor analysis, with internal reliability of included items reported. The convergent validity of K-Scale was tested against self-rated internet addiction, and S-Scale using multiple regression models. The results showed that a second-order two-factor 13-item structure was the most parsimonious model (NFI=0.919, NNFI=0.935, CFI=0.949, and RMSEA=0.05) with good internal reliability (Cronbach's alpha=0.87). The two factors revealed were "Disturbance of Adaptation and Life Orientation" and "Withdrawal and Tolerance". Moreover, the correlation between internet user classifications defined by K-Scale and self-rating was significant. K-Scale total score was significantly and positively associated with S-Scale total (adjusted R 2 =0.440) and subscale scores (adjusted R 2 =0.439). In conclusion, K-Scale is a valid and reliable assessment scale of internet addiction for Japanese high school students after modifications. Copyright © 2017. Published by Elsevier B.V.

Can basin land use effects on physical characteristics of streams be determined at broad geographic scales?

USGS Publications Warehouse

Goldstein, R.M.; Carlisle, D.M.; Meador, M.R.; Short, T.M.

2007-01-01

The environmental setting (e.g., climate, topography, geology) and land use affect stream physical characteristics singly and cumulatively. At broad geographic scales, we determined the importance of environmental setting and land use in explaining variation in stream physical characteristics. We hypothesized that as the spatial scale decreased from national to regional, land use would explain more of the variation in stream physical characteristics because environmental settings become more homogeneous. At a national scale, stepwise linear regression indicated that environmental setting was more important in explaining variability in stream physical characteristics. Although statistically discernible, the amount of variation explained by land use was not remarkable due to low partial correlations. At level II ecoregion spatial scales (southeastern USA plains, central USA plains, and a combination of the western Cordillera and the western interior basins and ranges), environmental setting variables were again more important predictors of stream physical characteristics, however, as the spatial scale decreased from national to regional, the portion of variability in stream physical characteristics explained by basin land use increased. Development of stream habitat indicators of land use will depend upon an understanding of relations between stream physical characteristics and environmental factors at multiple spatial scales. Smaller spatial scales will be necessary to reduce the confounding effects of variable environmental settings before the effects of land use can be reliably assessed. ?? Springer Science+Business Media B.V. 2006.

Sense of Coherence as a Determinant of Psychological Well-Being Across Professional Groups of Aid Workers Exposed to War Trauma.

PubMed

Veronese, Guido; Pepe, Alessandro

2015-06-18

The present study aims to test whether sense of coherence (SOC) acts as a determinant of positive psychological functioning in aid workers directly exposed to warfare. Specifically, we performed multiple regression analyses to compare different groups of aid workers in terms of the effects of SOC and cumulative trauma on their psychological distress. Palestinian helpers, both professional and non-professional (N = 159) completed three self-reported measures: the General Health questionnaire, Sense of Coherence Scale, and Impact of Events Scale. The findings bear out the predictive power of SOC and posttraumatic stress disorder (PTSD) in relation to mental health across different professional groups. In particular, volunteers without a specific professional profile, psychiatrists, medical doctors, and less markedly counselors seemed to protect their mental health through a SOC. Clinical implications and recommendations for training and supervision are discussed. © The Author(s) 2015.

A prospective study of personality as a predictor of quality of life after pelvic pouch surgery.

PubMed

Weinryb, R M; Gustavsson, J P; Liljeqvist, L; Poppen, B; Rössel, R J

1997-02-01

Surgeons often "know" preoperatively which patients will achieve good postoperative quality of life (QOL). This intuition is probably based on impressions of the patient's personality. The present aim was to examine whether preoperative personality traits predict postoperative QOL. In 53 patients undergoing pelvic pouch surgery for ulcerative colitis the relationship between preoperative personality traits, and surgical functional outcome and QOL was examined at a median of 17 months postoperatively. Personality assessment instruments (KAPP and KSP), and specific measures of alexithymia were used. Postoperatively, the Psychosocial Adjustment to Illness Scale (PAIS), and surgical functional outcome scales were used. Using multiple correlation/regression, analysis lack of alexithymia, poor frustration tolerance, anxiety proneness, and poor socialization (resentment over childhood and present life situation) were found to predict poor postoperative QOL. The findings suggest personality traits, in addition to surgical functional outcome, to be important for the patient's postoperative QOL.

Contribution of problem-solving skills to fear of recurrence in breast cancer survivors.

PubMed

Akechi, Tatuo; Momino, Kanae; Yamashita, Toshinari; Fujita, Takashi; Hayashi, Hironori; Tsunoda, Nobuyuki; Iwata, Hiroji

2014-05-01

Although fear of recurrence is a major concern among breast cancer survivors after surgery, no standard strategies exist that alleviate their distress. This study examined the association of patients' problem-solving skills and fear of recurrence and psychological distress among breast cancer survivors. Randomly selected, ambulatory, female patients with breast cancer participated in this study. They were asked to complete the Concerns about Recurrence Scale (CARS) and the Hospital Anxiety and Depression Scale. Multiple regression analyses were used to examine their associations. Data were obtained from 317 patients. Patients' problem-solving skills were significantly associated with all subscales of fear of recurrence and overall worries measured by the CARS. In addition, patients' problem-solving skills were significantly associated with both their anxiety and depression. Our findings warrant clinical trials to investigate effectiveness of psychosocial intervention program, including enhancing patients' problem-solving skills and reducing fear of recurrence among breast cancer survivors.

Self-transcendence and well-being in homeless adults.

PubMed

Runquist, Jennifer J; Reed, Pamela G

2007-03-01

This study examines the relationships of spiritually and physically related variables to well-being among homeless adults. A convenience sample of 61 sheltered homeless persons completed the Spiritual Perspective Scale, the Self-Transcendence Scale, the Index of Well-Being, and items measuring fatigue and health status. The data were subjected to correlational and multiple regression analysis. Positive, significant correlations were found among spiritual perspective, self-transcendence, health status, and well-being. Fatigue was inversely correlated with health status and well-being. Self-transcendence and health status together explained 59% of the variance in well-being. The findings support Reed's theory of self-transcendence, in which there is the basic assumption that human beings have the potential to integrate difficult life situations. This study contributes to the growing body of evidence that conceptualizes homeless persons as having spiritual, emotional, and physical capacities that can be used by health care professionals to promote well-being in this vulnerable population.

Self-transcendence and depression in middle-age adults.

PubMed

Ellermann, C R; Reed, P G

2001-11-01

Self-transcendence has been found to be an important correlate of mental health in older adults and adults facing the end of life. This study extends current theory by examining the relationship of transcendence and other transcendence variables to depression in middle-age adults (N = 133). Reed's Self-Transcendence Scale, the Center for Epidemiological Studies-Depression Scale, and measures of parenting, acceptance and spirituality were administered. Findings indicating significant inverse correlations between self-transcendence and depression, as well as between other measures of transcendence and depression support Reed's (1991b) theory. Multiple regression analysis indicated that acceptance may be another significant correlate of depression. Significant gender differences and age-related patterns of increased levels of self-transcendence were found. Study results illuminate the need to continue research into developmentally based transcendence variables related to various experiences of health and well-being across the life span.

The relationship between ADHD symptoms, mood instability, and self-reported offending.

PubMed

Gudjonsson, Gisli H; Sigurdsson, Jon Fridrik; Adalsteinsson, Tomas F; Young, Susan

2013-05-01

To investigate the relative importance of ADHD symptoms, mood instability, and antisocial personality disorder traits in predicting self-reported offending. A total of 295 Icelandic students completed two scales of offending behavior and measures of ADHD symptoms, mood instability, and antisocial personality traits. Self-reported offending from the two independent scales correlated significantly with ADHD symptoms, mood instability, and antisocial personality traits with medium to large effect size. Multiple regressions showed that ADHD symptoms contributed to the two outcome measures beyond that of age and gender with a medium effect size. The ADHD effects were only partly mediated by mood instability and antisocial personality traits for general offending but were almost completely mediated by the more reactive measure of antisocial behavior. ADHD appears to be a potential risk factor for general offending in its own right irrespective of the presence of comorbidity, whereas mood instability is more important with regard to reactive behavior.

Appreciation of historical events and characters: their relationship with national identity and collective self-esteem in a sample of public school teachers from the city of Lima.

PubMed

Rottenbacher de Rojas, Jan Marc

2010-11-01

This study analyzes the relation between national identity and the appreciation of the characters and events of Peruvian history in a sample of public school teachers from the city of Lima (N = 99). Adapted versions of the NATID Scale (Keillor et al., 1996) and the CSES Scale (Luhtanen & Crocker, 1992) are used as measures of national identity. National pride and interest in knowing about Peruvian history are variables also included in this study. The study shows that appreciation of historical characters is more positive than appreciation of historical events. There is a positive association between national identity and appreciation of Peruvian historical characters. A multiple linear regression model is proposed; this model shows that appreciation of cultural heritage and national pride has a positive impact on the appreciation of characters of Peruvian history.

Psychological Factors and Alcohol Use in Problematic Mobile Phone Use in the Spanish Population

PubMed Central

De-Sola, José; Talledo, Hernán; Rubio, Gabriel; de Fonseca, Fernando Rodríguez

2017-01-01

This research aims to study the existing relationships among the factors of state anxiety, depression, impulsivity, and alcohol consumption regarding problematic mobile phone use, as assessed by the Mobile Phone Problem Use Scale. The study was conducted among 1,126 participants recruited among the general Spanish population, aged 16–65 years, by assessing the predictive value of these variables regarding this problematic use. Initially tobacco use was also considered being subsequently refused because of the low internal consistency of the scale used. In general terms, the results show that this problematic use is mainly related to state anxiety and impulsivity, through the dimensions of Positive and Negative Urgency. Considering its predictive value, multiple regression analysis reveals that state anxiety, positive and negative urgency, and alcohol consumption may predict problematic mobile phone use, ruling out the influence of depression. PMID:28217101

The importance of the function of exercise in the relationship between obligatory exercise and eating and body image concerns.

PubMed

De Young, Kyle P; Anderson, Drew A

2010-01-01

This study tested whether exercising in response to negative affect moderates the association between obligatory exercise and eating and body image psychopathology. Participants (n=226) completed the Eating Disorders Examination-Questionnaire (EDE-Q), Obligatory Exercise Questionnaire (OEQ), and a question assessing whether they ever exercise in response to negative affect. In total, 132 (58.4%) participants endorsed exercising in response to negative affect. Multiple regression analyses revealed significant main effects of negative affect motivated exercise, OEQ total scores, and gender on all four EDE-Q subscales and significant interactions of negative affect motivated exercise and OEQ scores on the Eating Concern, Shape Concern, and Weight Concern scales but not the Restraint scale of the EDE-Q. Obligatory exercisers may not demonstrate elevated eating and body image concerns in the absence of negative affect motivated exercise, providing further support of the importance of the function of exercise.

Dimensions of the epilepsy foundation concerns index.

PubMed

Loring, David W; Larrabee, Glenn J; Meador, Kimford J; Lee, Gregory P

2005-05-01

We performed principal component analysis (PCA) of the Epilepsy Foundation Concerns Index scale in 189 patients undergoing evaluation for epilepsy surgery. We identified a five-factor solution in which there were no varimax-rotated factors consisting of fewer than two questions. Factor 1 reflects affective impact on enjoyment of life, Factor 2 reflects general autonomy concerns, Factor 3 reflects fear of seizure recurrence, Factor 4 reflects concern of being a burden to one's family, and Factor 5 reflects a perceived lack of understanding by others. Multiple regression using the Quality of Life in Epilepsy--89 question version; Minnesota Multiphasic Personality Inventory--2; Wechsler Adult Intelligence Scale--third edition; and verbal and visual memory tests as predictors demonstrated a different pattern of association with the factor and summary scores. We conclude that the Epilepsy Foundation Concerns Index is multidimensional, and using a global score based on all items may mask specific concerns that may be relevant when applied to individual patients.

Relationship between emotional intelligence and organizational citizenship behavior.

PubMed

Turnipseed, David L; Vandewaa, Elizabeth A

2012-06-01

This study evaluated hypothesized positive linkages between organizational citizenship behavior and the emotional intelligence dimensions of perception, using emotion, understanding emotion, and management of emotion, involving two samples. Sample 1 comprised 334 employed college students, 52% male, with a mean age of 23.4 yr., who worked an average of 29.6 hr. per week. Sample 2 comprised 72 professors, 81% female, with a mean age of 47 yr. Measures were the Emotional Intelligence Scale and the Organizational Citizenship Behavior Scale. Results of hierarchical multiple regressions indicated a positive link between organizational citizenship behavior and emotional intelligence. There were differences between the samples. In Sample 1, each of the emotional intelligence dimensions were positively linked to citizenship behavior: using and managing emotion were the greatest contributors. In Sample 2, managing emotion was the only contributor. Emotional intelligence had the strongest relationship with citizenship behavior directed at individuals.

Academic procrastination: the relationship between causal attribution styles and behavioral postponement.

PubMed

Badri Gargari, Rahim; Sabouri, Hossein; Norzad, Fatemeh

2011-01-01

This research was conducted to study the relationship between attribution and academic procrastination in University Students. The subjects were 203 undergraduate students, 55 males and 148 females, selected from English and French language and literature students of Tabriz University. Data were gathered through Procrastination Assessment Scale-student (PASS) and Causal Dimension Scale (CDA) and were analyzed by multiple regression analysis (stepwise). The results showed that there was a meaningful and negative relation between the locus of control and controllability in success context and academic procrastination. Besides, a meaningful and positive relation was observed between the locus of control and stability in failure context and procrastination. It was also found that 17% of the variance of procrastination was accounted by linear combination of attributions. We believe that causal attribution is a key in understanding procrastination in academic settings and is used by those who have the knowledge of Causal Attribution styles to organize their learning.

Genetic and environmental variance in content dimensions of the MMPI.

PubMed

Rose, R J

1988-08-01

To evaluate genetic and environmental variance in the Minnesota Multiphasic Personality Inventory (MMPI), I studied nine factor scales identified in the first item factor analysis of normal adult MMPIs in a sample of 820 adolescent and young adult co-twins. Conventional twin comparisons documented heritable variance in six of the nine MMPI factors (Neuroticism, Psychoticism, Extraversion, Somatic Complaints, Inadequacy, and Cynicism), whereas significant influence from shared environmental experience was found for four factors (Masculinity versus Femininity, Extraversion, Religious Orthodoxy, and Intellectual Interests). Genetic variance in the nine factors was more evident in results from twin sisters than those of twin brothers, and a developmental-genetic analysis, using hierarchical multiple regressions of double-entry matrixes of the twins' raw data, revealed that in four MMPI factor scales, genetic effects were significantly modulated by age or gender or their interaction during the developmental period from early adolescence to early adulthood.

Desire thinking as a predictor of gambling.

PubMed

Fernie, Bruce A; Caselli, Gabriele; Giustina, Lucia; Donato, Gilda; Marcotriggiani, Antonella; Spada, Marcantonio M

2014-04-01

Desire thinking is a voluntary cognitive process involving verbal and imaginal elaboration of a desired target. A desired target can relate to an object, an internal state or an activity, such as gambling. This study investigated the role of desire thinking in gambling in a cohort of participants recruited from community and clinical settings. Ninety five individuals completed a battery of self-report measures consisting of the Hospital Anxiety and Depression Scale (HADS), the Gambling Craving Scale (GCS), the Desire Thinking Questionnaire (DTQ) and the South Oaks Gambling Screen (SOGS). Correlation analyses revealed that gender, educational level, recruitment source, anxiety and depression, craving and desire thinking were correlated with gambling. A hierarchical multiple regression analysis revealed that both recruitment source and desire thinking were the only independent predictors of gambling when controlling for all other study variables, including craving. These findings are discussed in the light of metacognitive therapy (MCT). Copyright © 2014 Elsevier Ltd. All rights reserved.

Psychological Factors and Alcohol Use in Problematic Mobile Phone Use in the Spanish Population.

PubMed

De-Sola, José; Talledo, Hernán; Rubio, Gabriel; de Fonseca, Fernando Rodríguez

2017-01-01

This research aims to study the existing relationships among the factors of state anxiety, depression, impulsivity, and alcohol consumption regarding problematic mobile phone use, as assessed by the Mobile Phone Problem Use Scale. The study was conducted among 1,126 participants recruited among the general Spanish population, aged 16-65 years, by assessing the predictive value of these variables regarding this problematic use. Initially tobacco use was also considered being subsequently refused because of the low internal consistency of the scale used. In general terms, the results show that this problematic use is mainly related to state anxiety and impulsivity, through the dimensions of Positive and Negative Urgency. Considering its predictive value, multiple regression analysis reveals that state anxiety, positive and negative urgency, and alcohol consumption may predict problematic mobile phone use, ruling out the influence of depression.

Microaggressions and marijuana use among college students.

PubMed

Pro, George; Sahker, Ethan; Marzell, Miesha

2017-03-09

This study examines the association between exposure to microaggressions and marijuana use, using original survey data from a sample of racial/ethnic minority college students (n = 332) from a large Division I university in the United States. Nearly all of our sample (96%) reported at least one experience with microaggressions in the past 6 months, while 33% reported using marijuana regularly. We modeled regular use of marijuana using multiple logistic regression, with consideration of sex, age, race/ethnicity, and microaggression scale scores as covariates. Age, sex, the microinvalidations subscale score, and the full microaggression scale score were significantly associated with marijuana use in our full models (p < .01; p = .01; p = .02; p = .03, respectively). With each additional experience of microaggression, the odds of regular marijuana use increase. Academic communities may consider the primary prevention of discriminatory behavior when addressing student substance use.

Modeling a historical mountain pine beetle outbreak using Landsat MSS and multiple lines of evidence

USGS Publications Warehouse

Assal, Timothy J.; Sibold, Jason; Reich, Robin M.

2014-01-01

Mountain pine beetles are significant forest disturbance agents, capable of inducing widespread mortality in coniferous forests in western North America. Various remote sensing approaches have assessed the impacts of beetle outbreaks over the last two decades. However, few studies have addressed the impacts of historical mountain pine beetle outbreaks, including the 1970s event that impacted Glacier National Park. The lack of spatially explicit data on this disturbance represents both a major data gap and a critical research challenge in that wildfire has removed some of the evidence from the landscape. We utilized multiple lines of evidence to model forest canopy mortality as a proxy for outbreak severity. We incorporate historical aerial and landscape photos, aerial detection survey data, a nine-year collection of satellite imagery and abiotic data. This study presents a remote sensing based framework to (1) relate measurements of canopy mortality from fine-scale aerial photography to coarse-scale multispectral imagery and (2) classify the severity of mountain pine beetle affected areas using a temporal sequence of Landsat data and other landscape variables. We sampled canopy mortality in 261 plots from aerial photos and found that insect effects on mortality were evident in changes to the Normalized Difference Vegetation Index (NDVI) over time. We tested multiple spectral indices and found that a combination of NDVI and the green band resulted in the strongest model. We report a two-step process where we utilize a generalized least squares model to account for the large-scale variability in the data and a binary regression tree to describe the small-scale variability. The final model had a root mean square error estimate of 9.8% canopy mortality, a mean absolute error of 7.6% and an R2 of 0.82. The results demonstrate that a model of percent canopy mortality as a continuous variable can be developed to identify a gradient of mountain pine beetle severity on the landscape.

Field- and Remote Sensing-based Structural Attributes Measured at Multiple Scales Influence the Relationship Between Nitrogen and Reflectance of Forest Canopies

NASA Astrophysics Data System (ADS)

Sullivan, F.; Ollinger, S. V.; Palace, M. W.; Ouimette, A.; Sanders-DeMott, R.; Lepine, L. C.

2017-12-01

The correlation between near-infrared reflectance and forest canopy nitrogen concentration has been demonstrated at varying scales using a range of optical sensors on airborne and satellite platforms. Although the mechanism underpinning the relationship is unclear, at its basis are biologically-driven functional relationships of multiple plant traits that affect canopy chemistry and structure. The link between near-infrared reflectance and canopy nitrogen has been hypothesized to be partially driven by covariation of canopy nitrogen with canopy structure. In this study, we used a combination of airborne LiDAR data and field measured leaf and canopy chemical and structural traits to explore interrelationships between canopy nitrogen, near-infrared reflectance, and canopy structure on plots at Bartlett Experimental Forest in the White Mountain National Forest, New Hampshire. Over each plot, we developed a 1-meter resolution canopy height profile and a 1-meter resolution canopy height model. From canopy height profiles and canopy height models, we calculated a set of metrics describing the plot-level variability, breadth, depth, and arrangement of LiDAR returns. This combination of metrics was used to describe both vertical and horizontal variation in structure. In addition, we developed and measured several field-based metrics of leaf and canopy structure at the plot scale by directly measuring the canopy or by weighting leaf-level metrics by species leaf area contribution. We assessed relationships between leaf and structural metrics, near-infrared reflectance and canopy nitrogen concentration using multiple linear regression and mixed effects modeling. Consistent with our hypothesis, we found moderately strong links between both near-infrared reflectance and canopy nitrogen concentration with LiDAR-derived structural metrics, and we additionally found that leaf-level metrics scaled to the plot level share an important role in canopy reflectance. We suggest that canopy structure has a governing role in canopy reflectance, reducing maximum potential reflectance as structural complexity increases, and therefore also influences the relationship between canopy nitrogen and NIR reflectance.

Predicting individualized clinical measures by a generalized prediction framework and multimodal fusion of MRI data

PubMed Central

Meng, Xing; Jiang, Rongtao; Lin, Dongdong; Bustillo, Juan; Jones, Thomas; Chen, Jiayu; Yu, Qingbao; Du, Yuhui; Zhang, Yu; Jiang, Tianzi; Sui, Jing; Calhoun, Vince D.

2016-01-01

Neuroimaging techniques have greatly enhanced the understanding of neurodiversity (human brain variation across individuals) in both health and disease. The ultimate goal of using brain imaging biomarkers is to perform individualized predictions. Here we proposed a generalized framework that can predict explicit values of the targeted measures by taking advantage of joint information from multiple modalities. This framework also enables whole brain voxel-wise searching by combining multivariate techniques such as ReliefF, clustering, correlation-based feature selection and multiple regression models, which is more flexible and can achieve better prediction performance than alternative atlas-based methods. For 50 healthy controls and 47 schizophrenia patients, three kinds of features derived from resting-state fMRI (fALFF), sMRI (gray matter) and DTI (fractional anisotropy) were extracted and fed into a regression model, achieving high prediction for both cognitive scores (MCCB composite r = 0.7033, MCCB social cognition r = 0.7084) and symptomatic scores (positive and negative syndrome scale [PANSS] positive r = 0.7785, PANSS negative r = 0.7804). Moreover, the brain areas likely responsible for cognitive deficits of schizophrenia, including middle temporal gyrus, dorsolateral prefrontal cortex, striatum, cuneus and cerebellum, were located with different weights, as well as regions predicting PANSS symptoms, including thalamus, striatum and inferior parietal lobule, pinpointing the potential neuromarkers. Finally, compared to a single modality, multimodal combination achieves higher prediction accuracy and enables individualized prediction on multiple clinical measures. There is more work to be done, but the current results highlight the potential utility of multimodal brain imaging biomarkers to eventually inform clinical decision-making. PMID:27177764

A Systematic Review of Global Drivers of Ant Elevational Diversity

PubMed Central

Szewczyk, Tim; McCain, Christy M.

2016-01-01

Ant diversity shows a variety of patterns across elevational gradients, though the patterns and drivers have not been evaluated comprehensively. In this systematic review and reanalysis, we use published data on ant elevational diversity to detail the observed patterns and to test the predictions and interactions of four major diversity hypotheses: thermal energy, the mid-domain effect, area, and the elevational climate model. Of sixty-seven published datasets from the literature, only those with standardized, comprehensive sampling were used. Datasets included both local and regional ant diversity and spanned 80° in latitude across six biogeographical provinces. We used a combination of simulations, linear regressions, and non-parametric statistics to test multiple quantitative predictions of each hypothesis. We used an environmentally and geometrically constrained model as well as multiple regression to test their interactions. Ant diversity showed three distinct patterns across elevations: most common were hump-shaped mid-elevation peaks in diversity, followed by low-elevation plateaus and monotonic decreases in the number of ant species. The elevational climate model, which proposes that temperature and precipitation jointly drive diversity, and area were partially supported as independent drivers. Thermal energy and the mid-domain effect were not supported as primary drivers of ant diversity globally. The interaction models supported the influence of multiple drivers, though not a consistent set. In contrast to many vertebrate taxa, global ant elevational diversity patterns appear more complex, with the best environmental model contingent on precipitation levels. Differences in ecology and natural history among taxa may be crucial to the processes influencing broad-scale diversity patterns. PMID:27175999

Universal Algorithms for Plant Phenotyping: Are we there yet?

NASA Astrophysics Data System (ADS)

Kakani, V. G.; Kambham, R. R.; Zhao, D.; Foster, A. J.; Gowda, P. H.

2017-12-01

Hyperspectral remote sensing offers ability to capture spectral signatures of plant morpho-physio-biochemical traits at multiple scales (leaf to canopy to aerial). Experimental results on plant phenotype from pot, growth chamber and field studies at multiple location were used in this study. Pigment, leaf/plant water status, plant nutrient status, plant height, leaf area, fresh and dry weights of biomass and its components are correlated with hyperspectral reflectance signatures. Leaf reflectance was collected with spectroradiometer having a light source. Canopy hyperspectral reflectance was collected from 1.5 m above the canopy using a spectroradiometer, while multispectral images were acquired from aerial platforms ( 400m). Several statistical methods including simple ratios, principal component analysis, and partial least squares regression were used to identify hyperspectral reflectance bands that were tightly associated with plant phenotypic traits. Leaf level spectra best described the morpho-physio-biochemical traits (R2 = 0.6-0.9), while canopy reflectance best described plant height (R2 = 0.65), leaf area index (R2 = 0.67-0.74) and biomass (R2 = 0.69-0.78), while aerial spectra improved canopy level regression coefficients for plant height (R2 = 0.93) and leaf area index (R2 = 0.89). The comparison of multi-level spectra and resolution, clearly showed the advantage of hyperspectral reflectance data over the multispectral reflectance data, particularly for understanding the basis for spectral reflectance differences among species and traits. In conclusion, high resolution (1-2 cm) spectral imagery can help to bridge the gap across multiple levels of phenotype measurement.

The impact of self-transcendence on physical health status promotion in multiple sclerosis patients attending peer support groups.

PubMed

JadidMilani, Maryam; Ashktorab, Tahereh; AbedSaeedi, Zhila; AlaviMajd, Hamid

2015-12-01

This study aimed to investigate the effect of self-transcendence on the physical health of multiple sclerosis (MS) patients attending peer support groups. This study was a quasi-experimental before-and-after design including 33 MS patients in three groups: 10 men in the men-only group, 11 women in the women-only group, and 12 men and women in the mixed group. Participants were required to attend eight weekly sessions of 2 h each. Instruments included the physical health section of the Multiple Sclerosis Quality of Life Inventory and Reed's Self-Transcendence Scale. Peer support group attendance was found to have a significant positive effect on the physical health and self-transcendence of MS patients when comparing average scores before and after attendance. Regression analysis showed that improvement in self-transcendence predicted improvement in physical health. Results show the positive effects of peer support groups on self-transcendence and physical health in MS patients, and suggest that improvement in well-being can be gained by promoting self-transcendence and physical health. © 2015 Wiley Publishing Asia Pty Ltd.

Internal predictors of burnout in psychiatric nurses: An Indian study

PubMed Central

Chakraborty, Rudraprosad; Chatterjee, Arunima; Chaudhury, Suprakash

2012-01-01

Background: Research has not adequately focused on the issue of burnout in Psychiatric nurses, despite the fact that they suffer considerable stress in their work. Till date no study has been conducted on burnout among psychiatric nurses in India. Further, there is a particular lack of research in internal variables predicting burnout in them. Aims: To determine whether there are any internal psychological factors relevant to burnout in psychiatric nurses in India. Materials and Methods: We recruited 101 psychiatric nurses scoring less than two in General Health Questionnaire, version 12 (GHQ-12) from two psychiatric hospitals after obtaining informed consent. All subjects filled up a sociodemographic data sheet along with global adjustment scale, emotional maturity scale, PGI general well-being scale, locus of control scale, and Copenhagen burnout inventory (CBI). Correlations between burnout and sociodemographic/clinical variables were done by Pearson's r or Spearman's rho. Signi ficant variables were entered in a stepwise multiple linear regression analysis with total burnout score as dependent variable. Results: Age, duration of total period of nursing, prior military training, locus of control, sense of general well-being, adjustment capabilities, and emotional maturity had significant relation with burnout. Of them, emotional maturity was the most significant protective factors against burnout along with adjustment capabilities, sense of physical well-being, and military training in decreasing significance. Together they explained 41% variation in total burnout score which is significant at <0.001 level. An internal locus of control was inversely correlated with burnout, but failed to predict it in regression analysis. Conclusion: Emotional maturity, adjustability, sense of general physical well-being as well as prior military training significantly predicted lower burnout. Of them, emotional maturity was the most important predictor. Internal locus of control was also correlated with lower burnout. PMID:24250044

Loneliness among very old Mexican Americans: findings from the Hispanic Established Populations Epidemiologic Studies of the Elderly.

PubMed

Gerst-Emerson, Kerstin; Shovali, Tamar E; Markides, Kyriakos S

2014-01-01

Increasing numbers of researchers are finding that loneliness is a significant risk factor for morbidity and mortality, and several variables have been found to be closely related to the experience of loneliness among elders. However, much of the research has focused on the general older population, with no research to date focusing on minority populations. The objective of this study was to determine the prevalence and the correlates of loneliness among a community-dwelling older Mexican American population. This study used a three-item loneliness scale to determine the prevalence of loneliness. Pearson's correlation and linear regression analyses were used to determine the cross-sectional association between sociodemographic, interpersonal relationship and health variables with the scale. Data used came from the most recent wave (2011) of the Hispanic Established Populations for the Epidemiological Study of the Elderly (H-EPESE). A total of 873 Mexican Americans completed the loneliness scale. The age range was from 80 to 102, with a majority (65%) female. The mean score on the scale was 4.05 (range 3-9), indicating relatively low levels of loneliness. Regression results indicate that depressive symptoms, cognitive status, and living alone were significantly associated with higher loneliness scores. Being married and having a confidante were significantly associated with lower loneliness. Age, number of close relatives and frequency of contact were not associated with loneliness. Findings suggest that among community-dwelling Mexican American older adults, loneliness has multiple determinants. Loneliness is a significant public health topic and clinicians should be aware of the various factors that can affect loneliness. Published by Elsevier Ireland Ltd.

Internal predictors of burnout in psychiatric nurses: An Indian study.

PubMed

Chakraborty, Rudraprosad; Chatterjee, Arunima; Chaudhury, Suprakash

2012-07-01

Research has not adequately focused on the issue of burnout in Psychiatric nurses, despite the fact that they suffer considerable stress in their work. Till date no study has been conducted on burnout among psychiatric nurses in India. Further, there is a particular lack of research in internal variables predicting burnout in them. To determine whether there are any internal psychological factors relevant to burnout in psychiatric nurses in India. We recruited 101 psychiatric nurses scoring less than two in General Health Questionnaire, version 12 (GHQ-12) from two psychiatric hospitals after obtaining informed consent. All subjects filled up a sociodemographic data sheet along with global adjustment scale, emotional maturity scale, PGI general well-being scale, locus of control scale, and Copenhagen burnout inventory (CBI). Correlations between burnout and sociodemographic/clinical variables were done by Pearson's r or Spearman's rho. Signi ficant variables were entered in a stepwise multiple linear regression analysis with total burnout score as dependent variable. Age, duration of total period of nursing, prior military training, locus of control, sense of general well-being, adjustment capabilities, and emotional maturity had significant relation with burnout. Of them, emotional maturity was the most significant protective factors against burnout along with adjustment capabilities, sense of physical well-being, and military training in decreasing significance. Together they explained 41% variation in total burnout score which is significant at <0.001 level. An internal locus of control was inversely correlated with burnout, but failed to predict it in regression analysis. Emotional maturity, adjustability, sense of general physical well-being as well as prior military training significantly predicted lower burnout. Of them, emotional maturity was the most important predictor. Internal locus of control was also correlated with lower burnout.

Assessing the socio-economic and demographic impact on health-related quality of life: evidence from Greece.

PubMed

Pappa, Evelina; Kontodimopoulos, Nick; Papadopoulos, Angelos A; Niakas, Dimitris

2009-01-01

The impact of socioeconomic status on health has been extensively studied and studies have shown that low socio-economic status is related to lower values of various health and quality-of-health measures. The aim of this study was to assess the influence of demographic and socio-economic factors on health- related quality of life (HRQoL). A cross-sectional study was carried out in 2003 using a representative sample of a Greek general population (n = 1007, 18+ years old), living in Athens area. Multivariate stepwise linear regression analyses were performed to investigate the influence of socio-demographic and economic variables on HRQoL, measured by eight scales of the SF-36. Interaction effects between socioeconomic status (SES) and demographic variables were also performed. Females and elderly people were associated with impaired HRQoL in all SF-36 scales. Disadvantaged SES i. e. primary education and low total household income was related to important decline in HRQoL and a similar relation was identified among men and women. Only the interaction effects between age and SES was statistically significant for some SF-36 scales. Multiple regression analyses produced models explaining significant portions of the variance in SF-36 scales, especially physical functioning. The analysis presented here gives evidence of a relationship existing between SES and HRQoL similar to what has been found elsewhere. In order to protect people from the damaging effects of poverty in health it is important to formulate health promotion educational programs or to direct policies to empower the disposable income etc. Helping people in disadvantaged SES to achieve the good health that people in more advantaged SES attained would help to prevent the widening of health inequalities.

Differential Item Functioning in the SF-36 Physical Functioning and Mental Health Sub-Scales: A Population-Based Investigation in the Canadian Multicentre Osteoporosis Study.

PubMed

Lix, Lisa M; Wu, Xiuyun; Hopman, Wilma; Mayo, Nancy; Sajobi, Tolulope T; Liu, Juxin; Prior, Jerilynn C; Papaioannou, Alexandra; Josse, Robert G; Towheed, Tanveer E; Davison, K Shawn; Sawatzky, Richard

2016-01-01

Self-reported health status measures, like the Short Form 36-item Health Survey (SF-36), can provide rich information about the overall health of a population and its components, such as physical, mental, and social health. However, differential item functioning (DIF), which arises when population sub-groups with the same underlying (i.e., latent) level of health have different measured item response probabilities, may compromise the comparability of these measures. The purpose of this study was to test for DIF on the SF-36 physical functioning (PF) and mental health (MH) sub-scale items in a Canadian population-based sample. Study data were from the prospective Canadian Multicentre Osteoporosis Study (CaMos), which collected baseline data in 1996-1997. DIF was tested using a multiple indicators multiple causes (MIMIC) method. Confirmatory factor analysis defined the latent variable measurement model for the item responses and latent variable regression with demographic and health status covariates (i.e., sex, age group, body weight, self-perceived general health) produced estimates of the magnitude of DIF effects. The CaMos cohort consisted of 9423 respondents; 69.4% were female and 51.7% were less than 65 years. Eight of 10 items on the PF sub-scale and four of five items on the MH sub-scale exhibited DIF. Large DIF effects were observed on PF sub-scale items about vigorous and moderate activities, lifting and carrying groceries, walking one block, and bathing or dressing. On the MH sub-scale items, all DIF effects were small or moderate in size. SF-36 PF and MH sub-scale scores were not comparable across population sub-groups defined by demographic and health status variables due to the effects of DIF, although the magnitude of this bias was not large for most items. We recommend testing and adjusting for DIF to ensure comparability of the SF-36 in population-based investigations.

Ridge: a computer program for calculating ridge regression estimates

Treesearch

Donald E. Hilt; Donald W. Seegrist

1977-01-01

Least-squares coefficients for multiple-regression models may be unstable when the independent variables are highly correlated. Ridge regression is a biased estimation procedure that produces stable estimates of the coefficients. Ridge regression is discussed, and a computer program for calculating the ridge coefficients is presented.

Development and validation of an environmental fragility index (EFI) for the neotropical savannah biome.

PubMed

Macedo, Diego R; Hughes, Robert M; Kaufmann, Philip R; Callisto, Marcos

2018-04-23

Augmented production and transport of fine sediments resulting from increased human activities are major threats to freshwater ecosystems, including reservoirs and their ecosystem services. To support large scale assessment of the likelihood of soil erosion and reservoir sedimentation, we developed and validated an environmental fragility index (EFI) for the Brazilian neotropical savannah. The EFI was derived from measured geoclimatic controls on sediment production (rainfall, variation of elevation and slope, geology) and anthropogenic pressures (natural cover, road density, distance from roads and urban centers) in 111 catchments upstream of four large hydroelectric reservoirs. We evaluated the effectiveness of the EFI by regressing it against a relative bed stability index (LRBS) that assesses the degree to which stream sites draining into the reservoirs are affected by excess fine sediments. We developed the EFI on 111 of these sites and validated our model on the remaining 37 independent sites. We also compared the effectiveness of the EFI in predicting LRBS with that of a multiple linear regression model (via best-subset procedure) using 7 independent variables. The EFI was significantly correlated with the LRBS, with regression R 2 values of 0.32 and 0.40, respectively, in development and validation sites. Although the EFI and multiple regression explained similar amounts of variability (R 2  = 0.32 vs 0.36), the EFI had a higher F-ratio (51.6 vs 8.5) and better AICc value (333 vs 338). Because the sites were randomly selected and well-distributed across geoclimatic controlling factors, we were able to calculate spatially-explicit EFI values for all hydrologic units within the study area (~38,500 km 2 ). This model-based inference showed that over 65% of those units had high or extreme fragility. This methodology has great potential for application in the management, recovery, and preservation of hydroelectric reservoirs and streams in tropical river basins. Copyright © 2018 Elsevier B.V. All rights reserved.

An empirical study using permutation-based resampling in meta-regression

PubMed Central

2012-01-01

Background In meta-regression, as the number of trials in the analyses decreases, the risk of false positives or false negatives increases. This is partly due to the assumption of normality that may not hold in small samples. Creation of a distribution from the observed trials using permutation methods to calculate P values may allow for less spurious findings. Permutation has not been empirically tested in meta-regression. The objective of this study was to perform an empirical investigation to explore the differences in results for meta-analyses on a small number of trials using standard large sample approaches verses permutation-based methods for meta-regression. Methods We isolated a sample of randomized controlled clinical trials (RCTs) for interventions that have a small number of trials (herbal medicine trials). Trials were then grouped by herbal species and condition and assessed for methodological quality using the Jadad scale, and data were extracted for each outcome. Finally, we performed meta-analyses on the primary outcome of each group of trials and meta-regression for methodological quality subgroups within each meta-analysis. We used large sample methods and permutation methods in our meta-regression modeling. We then compared final models and final P values between methods. Results We collected 110 trials across 5 intervention/outcome pairings and 5 to 10 trials per covariate. When applying large sample methods and permutation-based methods in our backwards stepwise regression the covariates in the final models were identical in all cases. The P values for the covariates in the final model were larger in 78% (7/9) of the cases for permutation and identical for 22% (2/9) of the cases. Conclusions We present empirical evidence that permutation-based resampling may not change final models when using backwards stepwise regression, but may increase P values in meta-regression of multiple covariates for relatively small amount of trials. PMID:22587815

Linking patient satisfaction with nursing care: the case of care rationing - a correlational study.

PubMed

Papastavrou, Evridiki; Andreou, Panayiota; Tsangari, Haritini; Merkouris, Anastasios

2014-01-01

Implicit rationing of nursing care is the withholding of or failure to carry out all necessary nursing measures due to lack of resources. There is evidence supporting a link between rationing of nursing care, nurses' perceptions of their professional environment, negative patient outcomes, and placing patient safety at risk. The aims of the study were: a) To explore whether patient satisfaction is linked to nurse-reported rationing of nursing care and to nurses' perceptions of their practice environment while adjusting for patient and nurse characteristics. b) To identify the threshold score of rationing by comparing the level of patient satisfaction factors across rationing levels. A descriptive, correlational design was employed. Participants in this study included 352 patients and 318 nurses from ten medical and surgical units of five general hospitals. Three measurement instruments were used: the BERNCA scale for rationing of care, the RPPE scale to explore nurses' perceptions of their work environment and the Patient Satisfaction scale to assess the level of patient satisfaction with nursing care. The statistical analysis included the use of Kendall's correlation coefficient to explore a possible relationship between the variables and multiple regression analysis to assess the effects of implicit rationing of nursing care together with organizational characteristics on patient satisfaction. The mean score of implicit rationing of nursing care was 0.83 (SD = 0.52, range = 0-3), the overall mean of RPPE was 2.76 (SD = 0.32, range = 1.28 - 3.69) and the two scales were significantly correlated (τ = -0.234, p < 0.001). The regression analysis showed that care rationing and work environment were related to patient satisfaction, even after controlling for nurse and patient characteristics. The results from the adjusted regression models showed that even at the lowest level of rationing (i.e. 0.5) patients indicated low satisfaction. The results support the relationships between organizational and environmental variables, care rationing and patient satisfaction. The identification of thresholds at which rationing starts to influence patient outcomes in a negative way may allow nurse managers to introduce interventions so as to keep rationing at a level at which patient safety is not jeopardized.

Gambling disorder-related illegal acts: Regression model of associated factors

PubMed Central

Gorsane, Mohamed Ali; Reynaud, Michel; Vénisse, Jean-Luc; Legauffre, Cindy; Valleur, Marc; Magalon, David; Fatséas, Mélina; Chéreau-Boudet, Isabelle; Guilleux, Alice; JEU Group; Challet-Bouju, Gaëlle; Grall-Bronnec, Marie

2017-01-01

Background and aims Gambling disorder-related illegal acts (GDRIA) are often crucial events for gamblers and/or their entourage. This study was designed to determine the predictive factors of GDRIA. Methods Participants were 372 gamblers reporting at least three DSM-IV-TR (American Psychiatric Association, 2000) criteria. They were assessed on the basis of sociodemographic characteristics, gambling-related characteristics, their personality profile, and psychiatric comorbidities. A multiple logistic regression was performed to identify the relevant predictors of GDRIA and their relative contribution to the prediction of the presence of GDRIA. Results Multivariate analysis revealed a higher South Oaks Gambling Scale score, comorbid addictive disorders, and a lower level of income as GDRIA predictors. Discussion and conclusion An original finding of this study was that the comorbid addictive disorder effect might be mediated by a disinhibiting effect of stimulant substances on GDRIA. Further studies are necessary to replicate these results, especially in a longitudinal design, and to explore specific therapeutic interventions. PMID:28198636