Environmental stress, inbreeding, and the nature of phenotypic and genetic variance in Drosophila melanogaster.

PubMed Central

Fowler, Kevin; Whitlock, Michael C

2002-01-01

Fifty-two lines of Drosophila melanogaster founded by single-pair population bottlenecks were used to study the effects of inbreeding and environmental stress on phenotypic variance, genetic variance and survivorship. Cold temperature and high density cause reduced survivorship, but these stresses do not cause repeatable changes in the phenotypic variance of most wing morphological traits. Wing area, however, does show increased phenotypic variance under both types of environmental stress. This increase is no greater in inbred than in outbred lines, showing that inbreeding does not increase the developmental effects of stress. Conversely, environmental stress does not increase the extent of inbreeding depression. Genetic variance is not correlated with environmental stress, although the amount of genetic variation varies significantly among environments and lines vary significantly in their response to environmental change. Drastic changes in the environment can cause changes in phenotypic and genetic variance, but not in a way reliably predicted by the notion of 'stress'. PMID:11934358

Stochastic variation in avian survival rates: Life-history predictions, population consequences, and the potential responses to human perturbations and climate change

USGS Publications Warehouse

Schmutz, Joel A.; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.

2009-01-01

Stochastic variation in survival rates is expected to decrease long-term population growth rates. This expectation influences both life-history theory and the conservation of species. From this expectation, Pfister (1998) developed the important life-history prediction that natural selection will have minimized variability in those elements of the annual life cycle (such as adult survival rate) with high sensitivity. This prediction has not been rigorously evaluated for bird populations, in part due to statistical difficulties related to variance estimation. I here overcome these difficulties, and in an analysis of 62 populations, I confirm her prediction by showing a negative relationship between the proportional sensitivity (elasticity) of adult survival and the proportional variance (CV) of adult survival. However, several species deviated significantly from this expectation, with more process variance in survival than predicted. For instance, projecting the magnitude of process variance in annual survival for American redstarts (Setophaga ruticilla) for 25 years resulted in a 44% decline in abundance without assuming any change in mean survival rate. For most of these species with high process variance, recent changes in harvest, habitats, or changes in climate patterns are the likely sources of environmental variability causing this variability in survival. Because of climate change, environmental variability is increasing on regional and global scales, which is expected to increase stochasticity in vital rates of species. Increased stochasticity in survival will depress population growth rates, and this result will magnify the conservation challenges we face.

A consistent transported PDF model for treating differential molecular diffusion

NASA Astrophysics Data System (ADS)

Wang, Haifeng; Zhang, Pei

2016-11-01

Differential molecular diffusion is a fundamentally significant phenomenon in all multi-component turbulent reacting or non-reacting flows caused by the different rates of molecular diffusion of energy and species concentrations. In the transported probability density function (PDF) method, the differential molecular diffusion can be treated by using a mean drift model developed by McDermott and Pope. This model correctly accounts for the differential molecular diffusion in the scalar mean transport and yields a correct DNS limit of the scalar variance production. The model, however, misses the molecular diffusion term in the scalar variance transport equation, which yields an inconsistent prediction of the scalar variance in the transported PDF method. In this work, a new model is introduced to remedy this problem that can yield a consistent scalar variance prediction. The model formulation along with its numerical implementation is discussed, and the model validation is conducted in a turbulent mixing layer problem.

USING THE THEORY OF PLANNED BEHAVIOR TO DETERMINE THE CONDOM USE BEHAVIOR AMONG COLLEGE STUDENTS

PubMed Central

Asare, Matthew

2015-01-01

The study utilized the Theory of Planned Behavior (TPB) to determine condom use behavior among college students. A total of 218 college students with mean age of 20.9 years old participated in the study. A 32- item cross-sectional survey was administered among the participants. The constructs of attitude towards behavior, perceived behavioral control, and subjective norm (p<0.001) significantly predicted intention to use condoms and they accounted for 64% of the variance. Behavioral intention significantly predicted condom use and it accounted for 15% of the variance. The TPB could be used to guide programs in promoting condom use among college students. PMID:26512197

Structural changes and out-of-sample prediction of realized range-based variance in the stock market

NASA Astrophysics Data System (ADS)

Gong, Xu; Lin, Boqiang

2018-03-01

This paper aims to examine the effects of structural changes on forecasting the realized range-based variance in the stock market. Considering structural changes in variance in the stock market, we develop the HAR-RRV-SC model on the basis of the HAR-RRV model. Subsequently, the HAR-RRV and HAR-RRV-SC models are used to forecast the realized range-based variance of S&P 500 Index. We find that there are many structural changes in variance in the U.S. stock market, and the period after the financial crisis contains more structural change points than the period before the financial crisis. The out-of-sample results show that the HAR-RRV-SC model significantly outperforms the HAR-BV model when they are employed to forecast the 1-day, 1-week, and 1-month realized range-based variances, which means that structural changes can improve out-of-sample prediction of realized range-based variance. The out-of-sample results remain robust across the alternative rolling fixed-window, the alternative threshold value in ICSS algorithm, and the alternative benchmark models. More importantly, we believe that considering structural changes can help improve the out-of-sample performances of most of other existing HAR-RRV-type models in addition to the models used in this paper.

Spatial and visuospatial working memory tests predict performance in classic multiple-object tracking in young adults, but nonspatial measures of the executive do not.

PubMed

Trick, Lana M; Mutreja, Rachna; Hunt, Kelly

2012-02-01

An individual-differences approach was used to investigate the roles of visuospatial working memory and the executive in multiple-object tracking. The Corsi Blocks and Visual Patterns Tests were used to assess visuospatial working memory. Two relatively nonspatial measures of the executive were used: operation span (OSPAN) and reading span (RSPAN). For purposes of comparison, the digit span test was also included (a measure not expected to correlate with tracking). The tests predicted substantial amounts of variance (R (2) = .33), and the visuospatial measures accounted for the majority (R (2) = .30), with each making a significant contribution. Although the executive measures correlated with each other, the RSPAN did not correlate with tracking. The correlation between OSPAN and tracking was similar in magnitude to that between digit span and tracking (p < .05 for both), and when regression was used to partial out shared variance between the two tests, the remaining variance predicted by the OSPAN was minimal (sr ( 2 ) = .029). When measures of spatial memory were included in the regression, the unique variance predicted by the OSPAN became negligible (sr ( 2 ) = .000004). This suggests that the executive, as measured by tests such as the OSPAN, plays little role in explaining individual differences in multiple-object tracking.

Potential Predictability of the Monsoon Subclimate Systems

NASA Technical Reports Server (NTRS)

Yang, Song; Lau, K.-M.; Chang, Y.; Schubert, S.

1999-01-01

While El Nino/Southern Oscillation (ENSO) phenomenon can be predicted with some success using coupled oceanic-atmospheric models, the skill of predicting the tropical monsoons is low regardless of the methods applied. The low skill of monsoon prediction may be either because the monsoons are not defined appropriately or because they are not influenced significantly by boundary forcing. The latter characterizes the importance of internal dynamics in monsoon variability and leads to many eminent chaotic features of the monsoons. In this study, we analyze results from nine AMIP-type ensemble experiments with the NASA/GEOS-2 general circulation model to assess the potential predictability of the tropical climate system. We will focus on the variability and predictability of tropical monsoon rainfall on seasonal-to-interannual time scales. It is known that the tropical climate is more predictable than its extratropical counterpart. However, predictability is different from one climate subsystem to another within the tropics. It is important to understand the differences among these subsystems in order to increase our skill of seasonal-to-interannual prediction. We assess potential predictability by comparing the magnitude of internal and forced variances as defined by Harzallah and Sadourny (1995). The internal variance measures the spread among the various ensemble members. The forced part of rainfall variance is determined by the magnitude of the ensemble mean rainfall anomaly and by the degree of consistency of the results from the various experiments.

A Cosmic Variance Cookbook

NASA Astrophysics Data System (ADS)

Moster, Benjamin P.; Somerville, Rachel S.; Newman, Jeffrey A.; Rix, Hans-Walter

2011-04-01

Deep pencil beam surveys (<1 deg2) are of fundamental importance for studying the high-redshift universe. However, inferences about galaxy population properties (e.g., the abundance of objects) are in practice limited by "cosmic variance." This is the uncertainty in observational estimates of the number density of galaxies arising from the underlying large-scale density fluctuations. This source of uncertainty can be significant, especially for surveys which cover only small areas and for massive high-redshift galaxies. Cosmic variance for a given galaxy population can be determined using predictions from cold dark matter theory and the galaxy bias. In this paper, we provide tools for experiment design and interpretation. For a given survey geometry, we present the cosmic variance of dark matter as a function of mean redshift \\bar{z} and redshift bin size Δz. Using a halo occupation model to predict galaxy clustering, we derive the galaxy bias as a function of mean redshift for galaxy samples of a given stellar mass range. In the linear regime, the cosmic variance of these galaxy samples is the product of the galaxy bias and the dark matter cosmic variance. We present a simple recipe using a fitting function to compute cosmic variance as a function of the angular dimensions of the field, \\bar{z}, Δz, and stellar mass m *. We also provide tabulated values and a software tool. The accuracy of the resulting cosmic variance estimates (δσ v /σ v ) is shown to be better than 20%. We find that for GOODS at \\bar{z}=2 and with Δz = 0.5, the relative cosmic variance of galaxies with m *>1011 M sun is ~38%, while it is ~27% for GEMS and ~12% for COSMOS. For galaxies of m * ~ 1010 M sun, the relative cosmic variance is ~19% for GOODS, ~13% for GEMS, and ~6% for COSMOS. This implies that cosmic variance is a significant source of uncertainty at \\bar{z}=2 for small fields and massive galaxies, while for larger fields and intermediate mass galaxies, cosmic variance is less serious.

Estimation of genetic connectedness diagnostics based on prediction errors without the prediction error variance-covariance matrix.

PubMed

Holmes, John B; Dodds, Ken G; Lee, Michael A

2017-03-02

An important issue in genetic evaluation is the comparability of random effects (breeding values), particularly between pairs of animals in different contemporary groups. This is usually referred to as genetic connectedness. While various measures of connectedness have been proposed in the literature, there is general agreement that the most appropriate measure is some function of the prediction error variance-covariance matrix. However, obtaining the prediction error variance-covariance matrix is computationally demanding for large-scale genetic evaluations. Many alternative statistics have been proposed that avoid the computational cost of obtaining the prediction error variance-covariance matrix, such as counts of genetic links between contemporary groups, gene flow matrices, and functions of the variance-covariance matrix of estimated contemporary group fixed effects. In this paper, we show that a correction to the variance-covariance matrix of estimated contemporary group fixed effects will produce the exact prediction error variance-covariance matrix averaged by contemporary group for univariate models in the presence of single or multiple fixed effects and one random effect. We demonstrate the correction for a series of models and show that approximations to the prediction error matrix based solely on the variance-covariance matrix of estimated contemporary group fixed effects are inappropriate in certain circumstances. Our method allows for the calculation of a connectedness measure based on the prediction error variance-covariance matrix by calculating only the variance-covariance matrix of estimated fixed effects. Since the number of fixed effects in genetic evaluation is usually orders of magnitudes smaller than the number of random effect levels, the computational requirements for our method should be reduced.

The evaluation of different forest structural indices to predict the stand aboveground biomass of even-aged Scotch pine (Pinus sylvestris L.) forests in Kunduz, Northern Turkey.

PubMed

Ercanli, İlker; Kahriman, Aydın

2015-03-01

We assessed the effect of stand structural diversity, including the Shannon, improved Shannon, Simpson, McIntosh, Margelef, and Berger-Parker indices, on stand aboveground biomass (AGB) and developed statistical prediction models for the stand AGB values, including stand structural diversity indices and some stand attributes. The AGB prediction model, including only stand attributes, accounted for 85 % of the total variance in AGB (R (2)) with an Akaike's information criterion (AIC) of 807.2407, Bayesian information criterion (BIC) of 809.5397, Schwarz Bayesian criterion (SBC) of 818.0426, and root mean square error (RMSE) of 38.529 Mg. After inclusion of the stand structural diversity into the model structure, considerable improvement was observed in statistical accuracy, including 97.5 % of the total variance in AGB, with an AIC of 614.1819, BIC of 617.1242, SBC of 633.0853, and RMSE of 15.8153 Mg. The predictive fitting results indicate that some indices describing the stand structural diversity can be employed as significant independent variables to predict the AGB production of the Scotch pine stand. Further, including the stand diversity indices in the AGB prediction model with the stand attributes provided important predictive contributions in estimating the total variance in AGB.

Can personality close the intention-behavior gap for healthy eating? An examination with the HEXACO personality traits.

PubMed

Monds, Lauren A; MacCann, Carolyn; Mullan, Barbara A; Wong, Cara; Todd, Jemma; Roberts, Richard D

2016-10-01

The aim of this study was to investigate the predictive and moderating effects of HEXACO personality factors, in addition to theory of planned behavior (TPB) variables, on fruit and vegetable consumption. American college students (N = 1036) from 24 institutions were administered the TPB, HEXACO and a self-reported fruit and vegetable consumption measure. The TPB predicted 11-17% of variance in fruit and vegetable consumption, with greater variance accounted for in healthy weight compared to overweight individuals. Personality did not significantly improve the prediction of behavior above TPB constructs; however, conscientiousness was a significant incremental predictor of intention in both healthy weight and overweight/obese groups. While support was found for the TPB as an important predictor of fruit and vegetable consumption in students, little support was found for personality factors. Such findings have implications for interventions designed to target students at risk of chronic disease.

Time and resource limits on working memory: cross-age consistency in counting span performance.

PubMed

Ransdell, Sarah; Hecht, Steven

2003-12-01

This longitudinal study separated resource demand effects from those of retention interval in a counting span task among 100 children tested in grade 2 and again in grades 3 and 4. A last card large counting span condition had an equivalent memory load to a last card small, but the last card large required holding the count over a longer retention interval. In all three waves of assessment, the last card large condition was found to be less accurate than the last card small. A model predicting reading comprehension showed that age was a significant predictor when entered first accounting for 26% of the variance, but counting span accounted for a further 22% of the variance. Span at Wave 1 accounted for significant unique variance at Wave 2 and at Wave 3. Results were similar for math calculation with age accounting for 31% of the variance and counting span accounting for a further 34% of the variance. Span at Wave 1 explained unique variance in math at Wave 2 and at Wave 3.

Anthropometry as a predictor of high speed performance.

PubMed

Caruso, J F; Ramey, E; Hastings, L P; Monda, J K; Coday, M A; McLagan, J; Drummond, J

2009-07-01

To assess anthropometry as a predictor of high-speed performance, subjects performed four seated knee- and hip-extension workouts with their left leg on an inertial exercise trainer (Impulse Technologies, Newnan GA). Workouts, done exclusively in either the tonic or phasic contractile mode, entailed two one-minute sets separated by a 90-second rest period and yielded three performance variables: peak force, average force and work. Subjects provided the following anthropometric data: height, weight, body mass index, as well as total, upper and lower left leg lengths. Via multiple regression, anthropometry attempted to predict the variance per performance variable. Anthropometry explained a modest (R2=0.27-0.43) yet significant degree of variance from inertial exercise trainer workouts. Anthropometry was a better predictor of peak force variance from phasic workouts, while it accounted for a significant degree of average force and work variance solely from tonic workouts. Future research should identify variables that account for the unexplained variance from high-speed exercise performance.

Predicting active school travel: the role of planned behavior and habit strength.

PubMed

Murtagh, Shemane; Rowe, David A; Elliott, Mark A; McMinn, David; Nelson, Norah M

2012-05-30

Despite strong support for predictive validity of the theory of planned behavior (TPB) substantial variance in both intention and behavior is unaccounted for by the model's predictors. The present study tested the extent to which habit strength augments the predictive validity of the TPB in relation to a currently under-researched behavior that has important health implications, namely children's active school travel. Participants (N = 126 children aged 8-9 years; 59 % males) were sampled from five elementary schools in the west of Scotland and completed questionnaire measures of all TPB constructs in relation to walking to school and both walking and car/bus use habit. Over the subsequent week, commuting steps on school journeys were measured objectively using an accelerometer. Hierarchical multiple regressions were used to test the predictive utility of the TPB and habit strength in relation to both intention and subsequent behavior. The TPB accounted for 41 % and 10 % of the variance in intention and objectively measured behavior, respectively. Together, walking habit and car/bus habit significantly increased the proportion of explained variance in both intention and behavior by 6 %. Perceived behavioral control and both walking and car/bus habit independently predicted intention. Intention and car/bus habit independently predicted behavior. The TPB significantly predicts children's active school travel. However, habit strength augments the predictive validity of the model. The results indicate that school travel is controlled by both intentional and habitual processes. In practice, interventions could usefully decrease the habitual use of motorized transport for travel to school and increase children's intention to walk (via increases in perceived behavioral control and walking habit, and decreases in car/bus habit). Further research is needed to identify effective strategies for changing these antecedents of children's active school travel.

Predicting College Success: The Relative Contributions of Five Social/Personality Factors, Five Cognitive/Learning Factors, and SAT Scores

PubMed Central

Hannon, Brenda

2014-01-01

To-date, studies have examined simultaneously the relative predictive powers of two or three factors on GPA. The present study examines the relative powers of five social/personality factors, five cognitive/learning factors, and SAT scores to predict freshmen and non-freshmen (sophomores, juniors, seniors) academic success (i.e., GPA). The results revealed many significant predictors of GPA for both freshmen and non-freshmen. However, subsequent regressions showed that only academic self-efficacy, epistemic belief of learning, and high-knowledge integration explained unique variance in GPA (19%-freshmen, 23.2%-non-freshmen). Further for freshmen, SAT scores explained an additional unique 10.6% variance after the influences attributed to these three predictors was removed whereas for non-freshmen, SAT scores failed to explain any additional variance. These results highlight the unique and important contributions of academic self-efficacy, epistemic belief of learning and high-knowledge integration to GPA beyond other previously-identified predictors. PMID:25568884

An extended version of the theory of planned behaviour: the role of self-efficacy and past behaviour in predicting the physical activity of Chinese adolescents.

PubMed

Wang, Lijuan; Zhang, Ying

2016-01-01

This study aimed to use an extended theory of planned behaviour (TPB), which incorporated additional self-efficacy and past behaviour, to predict the intention to engage in moderate-to-vigorous physical activity (MVPA) and the MVPA level of Chinese adolescents. Questionnaires that focused on MVPA, attitude, subjective norm, perceived behavioural control (PBC), self-efficacy and past behaviour related to the MVPA engagement were administered to a sample of 488 young people. Multiple regression analyses provided moderate support for TPB. Three TPB constructs predicted 28.7% of the variance in intentions to engage in MVPA, and that PBC, but not intention, explained 3.4% of the variance in MVPA. Self-efficacy significantly affected intention and behaviour over and above the influence of TPB. Past behaviour had a small but significant improvement in the prediction of intention, but no improvement in the prediction of MVPA. Based on the results, interventions should target adolescent self-efficacy and PBC in physical activity participation.

Eye-hand coordination during a double-step task: evidence for a common stochastic accumulator

PubMed Central

Gopal, Atul

2015-01-01

Many studies of reaching and pointing have shown significant spatial and temporal correlations between eye and hand movements. Nevertheless, it remains unclear whether these correlations are incidental, arising from common inputs (independent model); whether these correlations represent an interaction between otherwise independent eye and hand systems (interactive model); or whether these correlations arise from a single dedicated eye-hand system (common command model). Subjects were instructed to redirect gaze and pointing movements in a double-step task in an attempt to decouple eye-hand movements and causally distinguish between the three architectures. We used a drift-diffusion framework in the context of a race model, which has been previously used to explain redirect behavior for eye and hand movements separately, to predict the pattern of eye-hand decoupling. We found that the common command architecture could best explain the observed frequency of different eye and hand response patterns to the target step. A common stochastic accumulator for eye-hand coordination also predicts comparable variances, despite significant difference in the means of the eye and hand reaction time (RT) distributions, which we tested. Consistent with this prediction, we observed that the variances of the eye and hand RTs were similar, despite much larger hand RTs (∼90 ms). Moreover, changes in mean eye RTs, which also increased eye RT variance, produced a similar increase in mean and variance of the associated hand RT. Taken together, these data suggest that a dedicated circuit underlies coordinated eye-hand planning. PMID:26084906

Combining clinical variables to optimize prediction of antidepressant treatment outcomes.

PubMed

Iniesta, Raquel; Malki, Karim; Maier, Wolfgang; Rietschel, Marcella; Mors, Ole; Hauser, Joanna; Henigsberg, Neven; Dernovsek, Mojca Zvezdana; Souery, Daniel; Stahl, Daniel; Dobson, Richard; Aitchison, Katherine J; Farmer, Anne; Lewis, Cathryn M; McGuffin, Peter; Uher, Rudolf

2016-07-01

The outcome of treatment with antidepressants varies markedly across people with the same diagnosis. A clinically significant prediction of outcomes could spare the frustration of trial and error approach and improve the outcomes of major depressive disorder through individualized treatment selection. It is likely that a combination of multiple predictors is needed to achieve such prediction. We used elastic net regularized regression to optimize prediction of symptom improvement and remission during treatment with escitalopram or nortriptyline and to identify contributing predictors from a range of demographic and clinical variables in 793 adults with major depressive disorder. A combination of demographic and clinical variables, with strong contributions from symptoms of depressed mood, reduced interest, decreased activity, indecisiveness, pessimism and anxiety significantly predicted treatment outcomes, explaining 5-10% of variance in symptom improvement with escitalopram. Similar combinations of variables predicted remission with area under the curve 0.72, explaining approximately 15% of variance (pseudo R(2)) in who achieves remission, with strong contributions from body mass index, appetite, interest-activity symptom dimension and anxious-somatizing depression subtype. Escitalopram-specific outcome prediction was more accurate than generic outcome prediction, and reached effect sizes that were near or above a previously established benchmark for clinical significance. Outcome prediction on the nortriptyline arm did not significantly differ from chance. These results suggest that easily obtained demographic and clinical variables can predict therapeutic response to escitalopram with clinically meaningful accuracy, suggesting a potential for individualized prescription of this antidepressant drug. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

The variance modulation associated with the vestibular evoked myogenic potential.

PubMed

Lütkenhöner, Bernd; Rudack, Claudia; Basel, Türker

2011-07-01

Model considerations suggest that the sound-induced inhibition underlying the vestibular evoked myogenic potential (VEMP) briefly reduces the variance of the electromyogram (EMG) from which the VEMP is derived. Although more difficult to investigate, this inhibitory modulation of the variance promises to be a specific measure of the inhibition, in that respect being superior to the VEMP itself. This study aimed to verify the theoretical predictions. Archived data from 672 clinical VEMP investigations, comprising about 300,000 EMG records altogether, were pooled. Both the complete data pool and subsets of data representing VEMPs of varying degrees of distinctness were analyzed. The data were generally normalized so that the EMG had variance one. Regarding VEMP deflection p13, the data confirm the theoretical predictions. At the latency of deflection n23, however, an additional excitatory component, showing a maximal effect around 30 ms, appears to contribute. Studying the variance modulation may help to identify and characterize different components of the VEMP. In particular, it appears to be possible to distinguish between inhibition and excitation. The variance modulation provides information not being available in the VEMP itself. Thus, studying this measure may significantly contribute to our understanding of the VEMP phenomenon. Copyright © 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Is Romantic Desire Predictable? Machine Learning Applied to Initial Romantic Attraction.

PubMed

Joel, Samantha; Eastwick, Paul W; Finkel, Eli J

2017-10-01

Matchmaking companies and theoretical perspectives on close relationships suggest that initial attraction is, to some extent, a product of two people's self-reported traits and preferences. We used machine learning to test how well such measures predict people's overall tendencies to romantically desire other people (actor variance) and to be desired by other people (partner variance), as well as people's desire for specific partners above and beyond actor and partner variance (relationship variance). In two speed-dating studies, romantically unattached individuals completed more than 100 self-report measures about traits and preferences that past researchers have identified as being relevant to mate selection. Each participant met each opposite-sex participant attending a speed-dating event for a 4-min speed date. Random forests models predicted 4% to 18% of actor variance and 7% to 27% of partner variance; crucially, however, they were unable to predict relationship variance using any combination of traits and preferences reported before the dates. These results suggest that compatibility elements of human mating are challenging to predict before two people meet.

Do Different Facets of Impulsivity Predict Different Types of Aggression?

PubMed Central

Derefinko, Karen; DeWall, C. Nathan; Metze, Amanda V.; Walsh, Erin C.; Lynam, Donald R.

2011-01-01

The current study examined the relations between impulsivity-related traits (as assessed by the UPPS-P Impulsive Behavior Scale) and aggressive behaviors. Results indicated that UPPS-P Lack of Premeditation and Sensation Seeking were important in predicting general violence. In contrast, UPPS-P Urgency was most useful in predicting intimate partner violence. To further explore relations between intimate partner violence and Urgency, a measure of autonomic response to pleasant and aversive stimuli and facets of Neuroticism from the NEO PI-R were used as control variables. Autonomic responsivity was correlated with intimate partner violence at the zero-order level, and predicted significant variance in intimate partner violence in regression equations. However, UPPS-P Urgency was able to account for unique variance in intimate partner violence above and beyond measures of Neuroticism and arousal. Implications regarding the use of a multifaceted conceptualization of impulsivity in the prediction of different types of violent behavior are discussed. PMID:21259270

Dancing with the Muses: dissociation and flow.

PubMed

Thomson, Paula; Jaque, S Victoria

2012-01-01

This study investigated dissociative psychological processes and flow (dispositional and state) in a group of professional and pre-professional dancers (n=74). In this study, high scores for global (Mdn=4.14) and autotelic (Mdn=4.50) flow suggest that dancing was inherently integrating and rewarding, although 17.6% of the dancers were identified as possibly having clinical levels of dissociation (Dissociative Experiences Scale-Taxon cutoff score≥20). The results of the multivariate analysis of variance indicated that subjects with high levels of dissociation had significantly lower levels of global flow (p<.05). Stepwise linear regression analyses demonstrated that dispositional flow negatively predicted the dissociative constructs of depersonalization and taxon (p<.05) but did not significantly predict the variance in absorption/imagination (p>.05). As hypothesized, dissociation and flow seem to operate as different mental processes.

Anthropometry as a predictor of vertical jump heights derived from an instrumented platform.

PubMed

Caruso, John F; Daily, Jeremy S; Mason, Melissa L; Shepherd, Catherine M; McLagan, Jessica R; Marshall, Mallory R; Walker, Ron H; West, Jason O

2012-01-01

The current study purpose examined the vertical height-anthropometry relationship with jump data obtained from an instrumented platform. Our methods required college-aged (n = 177) subjects to make 3 visits to our laboratory to measure the following anthropometric variables: height, body mass, upper arm length (UAL), lower arm length, upper leg length, and lower leg length. Per jump, maximum height was measured in 3 ways: from the subjects' takeoff, hang times, and as they landed on the platform. Standard multivariate regression assessed how well anthropometry predicted the criterion variance per gender (men, women, pooled) and jump height method (takeoff, hang time, landing) combination. Z-scores indicated that small amounts of the total data were outliers. The results showed that the majority of outliers were from jump heights calculated as women landed on the platform. With the genders pooled, anthropometry predicted a significant (p < 0.05) amount of variance from jump heights calculated from both takeoff and hang time. The anthropometry-vertical jump relationship was not significant from heights calculated as subjects landed on the platform, likely due to the female outliers. Yet anthropometric data of men did predict a significant amount of variance from heights calculated when they landed on the platform; univariate correlations of men's data revealed that UAL was the best predictor. It was concluded that the large sample of men's data led to greater data heterogeneity and a higher univariate correlation. Because of our sample size and data heterogeneity, practical applications suggest that coaches may find our results best predict performance for a variety of college-aged athletes and vertical jump enthusiasts.

A two step Bayesian approach for genomic prediction of breeding values.

PubMed

Shariati, Mohammad M; Sørensen, Peter; Janss, Luc

2012-05-21

In genomic models that assign an individual variance to each marker, the contribution of one marker to the posterior distribution of the marker variance is only one degree of freedom (df), which introduces many variance parameters with only little information per variance parameter. A better alternative could be to form clusters of markers with similar effects where markers in a cluster have a common variance. Therefore, the influence of each marker group of size p on the posterior distribution of the marker variances will be p df. The simulated data from the 15th QTL-MAS workshop were analyzed such that SNP markers were ranked based on their effects and markers with similar estimated effects were grouped together. In step 1, all markers with minor allele frequency more than 0.01 were included in a SNP-BLUP prediction model. In step 2, markers were ranked based on their estimated variance on the trait in step 1 and each 150 markers were assigned to one group with a common variance. In further analyses, subsets of 1500 and 450 markers with largest effects in step 2 were kept in the prediction model. Grouping markers outperformed SNP-BLUP model in terms of accuracy of predicted breeding values. However, the accuracies of predicted breeding values were lower than Bayesian methods with marker specific variances. Grouping markers is less flexible than allowing each marker to have a specific marker variance but, by grouping, the power to estimate marker variances increases. A prior knowledge of the genetic architecture of the trait is necessary for clustering markers and appropriate prior parameterization.

Predicting sugar-sweetened behaviours with theory of planned behaviour constructs: Outcome and process results from the SIPsmartER behavioural intervention.

PubMed

Zoellner, Jamie M; Porter, Kathleen J; Chen, Yvonnes; Hedrick, Valisa E; You, Wen; Hickman, Maja; Estabrooks, Paul A

2017-05-01

Guided by the theory of planned behaviour (TPB) and health literacy concepts, SIPsmartER is a six-month multicomponent intervention effective at improving SSB behaviours. Using SIPsmartER data, this study explores prediction of SSB behavioural intention (BI) and behaviour from TPB constructs using: (1) cross-sectional and prospective models and (2) 11 single-item assessments from interactive voice response (IVR) technology. Quasi-experimental design, including pre- and post-outcome data and repeated-measures process data of 155 intervention participants. Validated multi-item TPB measures, single-item TPB measures, and self-reported SSB behaviours. Hypothesised relationships were investigated using correlation and multiple regression models. TPB constructs explained 32% of the variance cross sectionally and 20% prospectively in BI; and explained 13-20% of variance cross sectionally and 6% prospectively. Single-item scale models were significant, yet explained less variance. All IVR models predicting BI (average 21%, range 6-38%) and behaviour (average 30%, range 6-55%) were significant. Findings are interpreted in the context of other cross-sectional, prospective and experimental TPB health and dietary studies. Findings advance experimental application of the TPB, including understanding constructs at outcome and process time points and applying theory in all intervention development, implementation and evaluation phases.

Discrimination in measures of knowledge monitoring accuracy

PubMed Central

Was, Christopher A.

2014-01-01

Knowledge monitoring predicts academic outcomes in many contexts. However, measures of knowledge monitoring accuracy are often incomplete. In the current study, a measure of students’ ability to discriminate known from unknown information as a component of knowledge monitoring was considered. Undergraduate students’ knowledge monitoring accuracy was assessed and used to predict final exam scores in a specific course. It was found that gamma, a measure commonly used as the measure of knowledge monitoring accuracy, accounted for a small, but significant amount of variance in academic performance whereas the discrimination and bias indexes combined to account for a greater amount of variance in academic performance. PMID:25339979

Effects of current exercise and diet on late-life cognitive health of former college football players.

PubMed

Hinton, Pamela S; Johnstone, Brick; Blaine, Edward; Bodling, Angela

2011-09-01

To determine the relative influence of current exercise and diet on the late-life cognitive health of former Division I collision-sport collegiate athletes (ie, football players) compared with noncollision-sport athletes and non-athletes. Graduates (n = 400) of a Midwestern university (average age, 64.09 years; standard deviation, 13.32) completed a self-report survey to assess current demographics/physical characteristics, exercise, diet, cognitive difficulties, and physical and mental health. Former football players reported more cognitive difficulties, as well as worse physical and mental health than controls. Among former football players, greater intake of total and saturated fat and cholesterol and lower overall diet quality were significantly correlated with cognitive difficulties; current dietary intake was not associated with cognitive health for the noncollision-sport athletes or nonathletes. Hierarchical regressions predicting cognitive difficulties indicated that income was positively associated with fewer cognitive difficulties and predicted 8% of the variance; status as a former football player predicted an additional 2% of the variance; and the interaction between being a football player and total dietary fat intake significantly predicted an additional 6% of the total variance (total model predicted 16% of variance). Greater intake of dietary fat was associated with increased cognitive difficulties, but only in the former football players, and not in the controls. Prior participation in football was associated with worse physical and mental health, while more frequent vigorous exercise was associated with higher physical and mental health ratings. Former football players reported more late-life cognitive difficulties and worse physical and mental health than former noncollision-sport athletes and nonathletes. A novel finding of the present study is that current dietary fat was associated with more cognitive difficulties, but only in the former football players. These results suggest the need for educational interventions to encourage healthy dietary habits to promote the long-term cognitive health of collision-sport athletes.

Relationships of Measurement Error and Prediction Error in Observed-Score Regression

ERIC Educational Resources Information Center

Moses, Tim

2012-01-01

The focus of this paper is assessing the impact of measurement errors on the prediction error of an observed-score regression. Measures are presented and described for decomposing the linear regression's prediction error variance into parts attributable to the true score variance and the error variances of the dependent variable and the predictor…

Learning Latent Variable and Predictive Models of Dynamical Systems

DTIC Science & Technology

2009-10-01

stable over the full 1000 frame image sequence without significant damping. C. Sam- ples drawn from a least squares synthesized sequences (top), and...LDS stabilizing algorithms, LB-1 and LB-2. Bars at every 20 timesteps denote variance in the results. CG provides the best stable short term predictions...observations. This thesis contributes (1) novel learning algorithms for existing dynamical system models that overcome significant limitations of previous

The Role of Emotion Reactivity in Health Anxiety.

PubMed

O'Bryan, Emily M; McLeish, Alison C; Johnson, Adrienne L

2017-11-01

Emotion reactivity, defined as heightened sensitivity, intensity, and persistence of emotional states, has been shown to contribute to the exacerbation of anxiety. However, the association between emotion reactivity and health anxiety has yet to be examined. The aim of the present investigation was to examine the unique predictive ability of emotion reactivity in terms of health anxiety in a sample of medically healthy undergraduates ( n = 194; 59.3% female, M age = 19.42, SD = 1.51, range = 18-26 years; 84.0% Caucasian). Findings indicated that, after controlling for the effects of gender, age, and anxiety sensitivity, greater emotion reactivity significantly predicted greater overall health anxiety (3.1% variance), as well as higher levels of affective (4.1% unique variance) and behavioral (4.8% unique variance) components. Findings suggest that experiencing emotions more frequently, intensely, and for longer durations of time prior to returning to baseline are associated with greater health preoccupations.

Global Genetic Variations Predict Brain Response to Faces

PubMed Central

Dickie, Erin W.; Tahmasebi, Amir; French, Leon; Kovacevic, Natasa; Banaschewski, Tobias; Barker, Gareth J.; Bokde, Arun; Büchel, Christian; Conrod, Patricia; Flor, Herta; Garavan, Hugh; Gallinat, Juergen; Gowland, Penny; Heinz, Andreas; Ittermann, Bernd; Lawrence, Claire; Mann, Karl; Martinot, Jean-Luc; Nees, Frauke; Nichols, Thomas; Lathrop, Mark; Loth, Eva; Pausova, Zdenka; Rietschel, Marcela; Smolka, Michal N.; Ströhle, Andreas; Toro, Roberto; Schumann, Gunter; Paus, Tomáš

2014-01-01

Face expressions are a rich source of social signals. Here we estimated the proportion of phenotypic variance in the brain response to facial expressions explained by common genetic variance captured by ∼500,000 single nucleotide polymorphisms. Using genomic-relationship-matrix restricted maximum likelihood (GREML), we related this global genetic variance to that in the brain response to facial expressions, as assessed with functional magnetic resonance imaging (fMRI) in a community-based sample of adolescents (n = 1,620). Brain response to facial expressions was measured in 25 regions constituting a face network, as defined previously. In 9 out of these 25 regions, common genetic variance explained a significant proportion of phenotypic variance (40–50%) in their response to ambiguous facial expressions; this was not the case for angry facial expressions. Across the network, the strength of the genotype-phenotype relationship varied as a function of the inter-individual variability in the number of functional connections possessed by a given region (R2 = 0.38, p<0.001). Furthermore, this variability showed an inverted U relationship with both the number of observed connections (R2 = 0.48, p<0.001) and the magnitude of brain response (R2 = 0.32, p<0.001). Thus, a significant proportion of the brain response to facial expressions is predicted by common genetic variance in a subset of regions constituting the face network. These regions show the highest inter-individual variability in the number of connections with other network nodes, suggesting that the genetic model captures variations across the adolescent brains in co-opting these regions into the face network. PMID:25122193

Sibling conflict in middle childhood predicts children's adjustment in early adolescence.

PubMed

Stocker, Clare M; Burwell, Rebecca A; Briggs, Megan L

2002-03-01

Associations between sibling conflict in middle childhood and psychological adjustment in early adolescence were studied in a sample of 80 boys and 56 girls. Parents and children provided self-report data about family relationships and children's adjustment. Parents' hostility to children was assessed from videotaped interactions. Results showed that sibling conflict at Time 1 predicted increases in children's anxiety, depressed mood, and delinquent behavior 2 years later. Moreover, earlier sibling conflict at Time 1 accounted for unique variance in young adolescents' Time 2 anxiety, depressed mood, and delinquent behavior above and beyond the variance explained by earlier maternal hostility and marital conflict. Children's adjustment at Time 1 did not predict sibling conflict at Time 2. Results highlight the unique significance of the earlier sibling relationship for young adolescents' psychological adjustment.

Island phytophagy: explaining the remarkable diversity of plant-feeding insects

PubMed Central

Joy, Jeffrey B.; Crespi, Bernard J.

2012-01-01

Plant-feeding insects have undergone unparalleled diversification among different plant taxa, yet explanations for variation in their diversity lack a quantitative, predictive framework. Island biogeographic theory has been applied to spatially discrete habitats but not to habitats, such as host plants, separated by genetic distance. We show that relationships between the diversity of gall-inducing flies and their host plants meet several fundamental predictions from island biogeographic theory. First, plant-taxon genetic distinctiveness, an integrator for long-term evolutionary history of plant lineages, is a significant predictor of variance in the diversity of gall-inducing flies among host-plant taxa. Second, range size and structural complexity also explain significant proportions of the variance in diversity of gall-inducing flies among different host-plant taxa. Third, as with other island systems, plant-lineage age does not predict species diversity. Island biogeographic theory, applied to habitats defined by genetic distance, provides a novel, comprehensive framework for analysing and explaining the diversity of plant-feeding insects and other host-specific taxa. PMID:22553094

Island phytophagy: explaining the remarkable diversity of plant-feeding insects.

PubMed

Joy, Jeffrey B; Crespi, Bernard J

2012-08-22

Plant-feeding insects have undergone unparalleled diversification among different plant taxa, yet explanations for variation in their diversity lack a quantitative, predictive framework. Island biogeographic theory has been applied to spatially discrete habitats but not to habitats, such as host plants, separated by genetic distance. We show that relationships between the diversity of gall-inducing flies and their host plants meet several fundamental predictions from island biogeographic theory. First, plant-taxon genetic distinctiveness, an integrator for long-term evolutionary history of plant lineages, is a significant predictor of variance in the diversity of gall-inducing flies among host-plant taxa. Second, range size and structural complexity also explain significant proportions of the variance in diversity of gall-inducing flies among different host-plant taxa. Third, as with other island systems, plant-lineage age does not predict species diversity. Island biogeographic theory, applied to habitats defined by genetic distance, provides a novel, comprehensive framework for analysing and explaining the diversity of plant-feeding insects and other host-specific taxa.

Ocean eddies and climate predictability

NASA Astrophysics Data System (ADS)

Kirtman, Ben P.; Perlin, Natalie; Siqueira, Leo

2017-12-01

A suite of coupled climate model simulations and experiments are used to examine how resolved mesoscale ocean features affect aspects of climate variability, air-sea interactions, and predictability. In combination with control simulations, experiments with the interactive ensemble coupling strategy are used to further amplify the role of the oceanic mesoscale field and the associated air-sea feedbacks and predictability. The basic intent of the interactive ensemble coupling strategy is to reduce the atmospheric noise at the air-sea interface, allowing an assessment of how noise affects the variability, and in this case, it is also used to diagnose predictability from the perspective of signal-to-noise ratios. The climate variability is assessed from the perspective of sea surface temperature (SST) variance ratios, and it is shown that, unsurprisingly, mesoscale variability significantly increases SST variance. Perhaps surprising is the fact that the presence of mesoscale ocean features even further enhances the SST variance in the interactive ensemble simulation beyond what would be expected from simple linear arguments. Changes in the air-sea coupling between simulations are assessed using pointwise convective rainfall-SST and convective rainfall-SST tendency correlations and again emphasize how the oceanic mesoscale alters the local association between convective rainfall and SST. Understanding the possible relationships between the SST-forced signal and the weather noise is critically important in climate predictability. We use the interactive ensemble simulations to diagnose this relationship, and we find that the presence of mesoscale ocean features significantly enhances this link particularly in ocean eddy rich regions. Finally, we use signal-to-noise ratios to show that the ocean mesoscale activity increases model estimated predictability in terms of convective precipitation and atmospheric upper tropospheric circulation.

Ocean eddies and climate predictability.

PubMed

Kirtman, Ben P; Perlin, Natalie; Siqueira, Leo

2017-12-01

A suite of coupled climate model simulations and experiments are used to examine how resolved mesoscale ocean features affect aspects of climate variability, air-sea interactions, and predictability. In combination with control simulations, experiments with the interactive ensemble coupling strategy are used to further amplify the role of the oceanic mesoscale field and the associated air-sea feedbacks and predictability. The basic intent of the interactive ensemble coupling strategy is to reduce the atmospheric noise at the air-sea interface, allowing an assessment of how noise affects the variability, and in this case, it is also used to diagnose predictability from the perspective of signal-to-noise ratios. The climate variability is assessed from the perspective of sea surface temperature (SST) variance ratios, and it is shown that, unsurprisingly, mesoscale variability significantly increases SST variance. Perhaps surprising is the fact that the presence of mesoscale ocean features even further enhances the SST variance in the interactive ensemble simulation beyond what would be expected from simple linear arguments. Changes in the air-sea coupling between simulations are assessed using pointwise convective rainfall-SST and convective rainfall-SST tendency correlations and again emphasize how the oceanic mesoscale alters the local association between convective rainfall and SST. Understanding the possible relationships between the SST-forced signal and the weather noise is critically important in climate predictability. We use the interactive ensemble simulations to diagnose this relationship, and we find that the presence of mesoscale ocean features significantly enhances this link particularly in ocean eddy rich regions. Finally, we use signal-to-noise ratios to show that the ocean mesoscale activity increases model estimated predictability in terms of convective precipitation and atmospheric upper tropospheric circulation.

The validity of physical aggression in predicting adolescent academic performance.

PubMed

Loveland, James M; Lounsbury, John W; Welsh, Deborah; Buboltz, Walter C

2007-03-01

Aggression has a long history in academic research as both a criterion and a predictor variable and it is well documented that aggression is related to a variety of poor academic outcomes such as: lowered academic performance, absenteeism and lower graduation rates. However, recent research has implicated physical aggression as being predictive of lower academic performance. The purpose of this study was to examine the role of the 'Big Five' personality traits of agreeableness, openness to experience, conscientiousness, neuroticism and extraversion and physical aggression in predicting the grade point averages (GPA) of adolescent students and to investigate whether or not there were differences in these relationships between male and female students. A sample of 992 students in grades 9 to 12 from a high school in south-eastern USA as part of a larger study examining the students' preparation for entry into the workforce. The study was correlational in nature: students completed a personality inventory developed by the second author with the GPA information supplied by the school. Results indicated that physical aggression accounts for 16% of variance in GPA and it adds 7% to the prediction of GPA beyond the Big Five. The Big Five traits added only 1.5% to the prediction of GPA after controlling for physical aggression. Interestingly, a significantly larger amount of variance in GPA was predicted by physical aggression for females than for males. Aggression accounts for significantly more variance in the GPA of females than for males, even when controlling for the Big Five personality factors. Future research should examine the differences in the expression of aggression in males and females, as well as how this is affecting interactions between peers and between students and their teachers.

Seasonal Predictability in a Model Atmosphere.

NASA Astrophysics Data System (ADS)

Lin, Hai

2001-07-01

The predictability of atmospheric mean-seasonal conditions in the absence of externally varying forcing is examined. A perfect-model approach is adopted, in which a global T21 three-level quasigeostrophic atmospheric model is integrated over 21 000 days to obtain a reference atmospheric orbit. The model is driven by a time-independent forcing, so that the only source of time variability is the internal dynamics. The forcing is set to perpetual winter conditions in the Northern Hemisphere (NH) and perpetual summer in the Southern Hemisphere.A significant temporal variability in the NH 90-day mean states is observed. The component of that variability associated with the higher-frequency motions, or climate noise, is estimated using a method developed by Madden. In the polar region, and to a lesser extent in the midlatitudes, the temporal variance of the winter means is significantly greater than the climate noise, suggesting some potential predictability in those regions.Forecast experiments are performed to see whether the presence of variance in the 90-day mean states that is in excess of the climate noise leads to some skill in the prediction of these states. Ensemble forecast experiments with nine members starting from slightly different initial conditions are performed for 200 different 90-day means along the reference atmospheric orbit. The serial correlation between the ensemble means and the reference orbit shows that there is skill in the 90-day mean predictions. The skill is concentrated in those regions of the NH that have the largest variance in excess of the climate noise. An EOF analysis shows that nearly all the predictive skill in the seasonal means is associated with one mode of variability with a strong axisymmetric component.

Predicting negative drinking consequences: examining descriptive norm perception.

PubMed

Benton, Stephen L; Downey, Ronald G; Glider, Peggy S; Benton, Sherry A; Shin, Kanghyun; Newton, Douglas W; Arck, William; Price, Amy

2006-05-01

This study explored how much variance in college student negative drinking consequences is explained by descriptive norm perception, beyond that accounted for by student gender and self-reported alcohol use. A derivation sample (N=7565; 54% women) and a replication sample (N=8924; 55.5% women) of undergraduate students completed the Campus Alcohol Survey in classroom settings. Hierarchical regression analyses revealed that student gender and average number of drinks when "partying" were significantly related to harmful consequences resulting from drinking. Men reported more consequences than did women, and drinking amounts were positively correlated with consequences. However, descriptive norm perception did not explain any additional variance beyond that attributed to gender and alcohol use. Furthermore, there was no significant three-way interaction among student gender, alcohol use, and descriptive norm perception. Norm perception contributed no significant variance in explaining harmful consequences beyond that explained by college student gender and alcohol use.

Testing a cognitive model to predict posttraumatic stress disorder following childbirth.

PubMed

King, Lydia; McKenzie-McHarg, Kirstie; Horsch, Antje

2017-01-14

One third of women describes their childbirth as traumatic and between 0.8 and 6.9% goes on to develop posttraumatic stress disorder (PTSD). The cognitive model of PTSD has been shown to be applicable to a range of trauma samples. However, childbirth is qualitatively different to other trauma types and special consideration needs to be taken when applying it to this population. Previous studies have investigated some cognitive variables in isolation but no study has so far looked at all the key processes described in the cognitive model. This study therefore aimed to investigate whether theoretically-derived variables of the cognitive model explain unique variance in postnatal PTSD symptoms when key demographic, obstetric and clinical risk factors are controlled for. One-hundred and fifty-seven women who were between 1 and 12 months post-partum (M = 6.5 months) completed validated questionnaires assessing PTSD and depressive symptoms, childbirth experience, postnatal social support, trauma memory, peritraumatic processing, negative appraisals, dysfunctional cognitive and behavioural strategies and obstetric as well as demographic risk factors in an online survey. A PTSD screening questionnaire suggested that 5.7% of the sample might fulfil diagnostic criteria for PTSD. Overall, risk factors alone predicted 43% of variance in PTSD symptoms and cognitive behavioural factors alone predicted 72.7%. A final model including both risk factors and cognitive behavioural factors explained 73.7% of the variance in PTSD symptoms, 37.1% of which was unique variance predicted by cognitive factors. All variables derived from Ehlers and Clark's cognitive model significantly explained variance in PTSD symptoms following childbirth, even when clinical, demographic and obstetric were controlled for. Our findings suggest that the CBT model is applicable and useful as a way of understanding and informing the treatment of PTSD following childbirth.

Perceived competence and enjoyment in predicting students' physical activity and cardiorespiratory fitness.

PubMed

Gao, Zan

2008-10-01

This study investigated the predictive strength of perceived competence and enjoyment on students' physical activity and cardiorespiratory fitness in physical education classes. Participants (N = 307; 101 in Grade 6, 96 in Grade 7, 110 in Grade 8; 149 boys, 158 girls) responded to questionnaires assessing perceived competence and enjoyment of physical education, then their cardiorespiratory fitness was assessed on the Progressive Aerobic Cardiovascular Endurance Run (PACER) test. Physical activity in one class was estimated via pedometers. Regression analyses showed enjoyment (R2 = 16.5) and perceived competence (R2 = 4.2) accounted for significant variance of only 20.7% of physical activity and, perceived competence was the only significant contributor to cardiorespiratory fitness performance (R2 = 19.3%). Only a small amount of variance here leaves 80% unaccounted for. Some educational implications and areas for research are mentioned.

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.

Mixed model approaches for diallel analysis based on a bio-model.

PubMed

Zhu, J; Weir, B S

1996-12-01

A MINQUE(1) procedure, which is minimum norm quadratic unbiased estimation (MINQUE) method with 1 for all the prior values, is suggested for estimating variance and covariance components in a bio-model for diallel crosses. Unbiasedness and efficiency of estimation were compared for MINQUE(1), restricted maximum likelihood (REML) and MINQUE theta which has parameter values for the prior values. MINQUE(1) is almost as efficient as MINQUE theta for unbiased estimation of genetic variance and covariance components. The bio-model is efficient and robust for estimating variance and covariance components for maternal and paternal effects as well as for nuclear effects. A procedure of adjusted unbiased prediction (AUP) is proposed for predicting random genetic effects in the bio-model. The jack-knife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects. Worked examples are given for estimation of variance and covariance components and for prediction of genetic merits.

The role of visual perception measures used in sports vision programmes in predicting actual game performance in Division I collegiate hockey players.

PubMed

Poltavski, Dmitri; Biberdorf, David

2015-01-01

Abstract In the growing field of sports vision little is still known about unique attributes of visual processing in ice hockey and what role visual processing plays in the overall athlete's performance. In the present study we evaluated whether visual, perceptual and cognitive/motor variables collected using the Nike SPARQ Sensory Training Station have significant relevance to the real game statistics of 38 Division I collegiate male and female hockey players. The results demonstrated that 69% of variance in the goals made by forwards in 2011-2013 could be predicted by their faster reaction time to a visual stimulus, better visual memory, better visual discrimination and a faster ability to shift focus between near and far objects. Approximately 33% of variance in game points was significantly related to better discrimination among competing visual stimuli. In addition, reaction time to a visual stimulus as well as stereoptic quickness significantly accounted for 24% of variance in the mean duration of the player's penalty time. This is one of the first studies to show that some of the visual skills that state-of-the-art generalised sports vision programmes are purported to target may indeed be important for hockey players' actual performance on the ice.

Are Career Centers Worthwhile?: Predicting Unique Variance in Career Outcomes through Career Center Usage

ERIC Educational Resources Information Center

Brotheridge, Celeste M.; Power, Jacqueline L.

2008-01-01

Purpose: This study seeks to examine the extent to which the use of career center services results in the significant incremental prediction of career outcomes beyond its established predictors. Design/methodology/approach: The authors survey the clients of a public agency's career center and use hierarchical multiple regressions in order to…

Psychosocial Correlates of HIV Protection Motivation among Black Adolescents in Venda, South Africa

ERIC Educational Resources Information Center

Boer, Henk; Mashamba, M. Tshilidzi

2005-01-01

We assessed the usefulness of the theory of planned behavior (TPB) and protection motivation theory (PMT) to predict intended condom use among 201 adolescents from Venda, South Africa. Results indicated that both the TPB and the PMT could significantly predict intended condom use, although the level of explained variance was limited. Hierarchical…

Predicting active school travel: The role of planned behavior and habit strength

PubMed Central

2012-01-01

Background Despite strong support for predictive validity of the theory of planned behavior (TPB) substantial variance in both intention and behavior is unaccounted for by the model’s predictors. The present study tested the extent to which habit strength augments the predictive validity of the TPB in relation to a currently under-researched behavior that has important health implications, namely children’s active school travel. Method Participants (N = 126 children aged 8–9 years; 59 % males) were sampled from five elementary schools in the west of Scotland and completed questionnaire measures of all TPB constructs in relation to walking to school and both walking and car/bus use habit. Over the subsequent week, commuting steps on school journeys were measured objectively using an accelerometer. Hierarchical multiple regressions were used to test the predictive utility of the TPB and habit strength in relation to both intention and subsequent behavior. Results The TPB accounted for 41 % and 10 % of the variance in intention and objectively measured behavior, respectively. Together, walking habit and car/bus habit significantly increased the proportion of explained variance in both intention and behavior by 6 %. Perceived behavioral control and both walking and car/bus habit independently predicted intention. Intention and car/bus habit independently predicted behavior. Conclusions The TPB significantly predicts children’s active school travel. However, habit strength augments the predictive validity of the model. The results indicate that school travel is controlled by both intentional and habitual processes. In practice, interventions could usefully decrease the habitual use of motorized transport for travel to school and increase children’s intention to walk (via increases in perceived behavioral control and walking habit, and decreases in car/bus habit). Further research is needed to identify effective strategies for changing these antecedents of children’s active school travel. PMID:22647194

Predicting sugar-sweetened behaviours with theory of planned behaviour constructs: Outcome and process results from the SIPsmartER behavioural intervention

PubMed Central

Zoellner, Jamie M.; Porter, Kathleen J.; Chen, Yvonnes; Hedrick, Valisa E.; You, Wen; Hickman, Maja; Estabrooks, Paul A.

2017-01-01

Objective Guided by the theory of planned behaviour (TPB) and health literacy concepts, SIPsmartER is a six-month multicomponent intervention effective at improving SSB behaviours. Using SIPsmartER data, this study explores prediction of SSB behavioural intention (BI) and behaviour from TPB constructs using: (1) cross-sectional and prospective models and (2) 11 single-item assessments from interactive voice response (IVR) technology. Design Quasi-experimental design, including pre- and post-outcome data and repeated-measures process data of 155 intervention participants. Main Outcome Measures Validated multi-item TPB measures, single-item TPB measures, and self-reported SSB behaviours. Hypothesised relationships were investigated using correlation and multiple regression models. Results TPB constructs explained 32% of the variance cross sectionally and 20% prospectively in BI; and explained 13–20% of variance cross sectionally and 6% prospectively. Single-item scale models were significant, yet explained less variance. All IVR models predicting BI (average 21%, range 6–38%) and behaviour (average 30%, range 6–55%) were significant. Conclusion Findings are interpreted in the context of other cross-sectional, prospective and experimental TPB health and dietary studies. Findings advance experimental application of the TPB, including understanding constructs at outcome and process time points and applying theory in all intervention development, implementation and evaluation phases. PMID:28165771

What predicts depression in cardiac patients: sociodemographic factors, disease severity or theoretical vulnerabilities?

PubMed

Doyle, F; McGee, H M; Conroy, R M; Delaney, M

2011-05-01

Depression is associated with increased cardiovascular risk in acute coronary syndrome (ACS) patients, but some argue that elevated depression is actually a marker of cardiovascular disease severity. Therefore, disease indices should better predict depression than established theoretical causes of depression (interpersonal life events, reinforcing events, cognitive distortions, type D personality). However, little theory-based research has been conducted in this area. In a cross-sectional design, ACS patients (n = 336) completed questionnaires assessing depression and psychosocial vulnerabilities. Nested logistic regression assessed the relative contribution of demographic or vulnerability factors, or disease indices or vulnerabilities to depression. In multivariate analysis, all vulnerabilities were independent significant predictors of depression (scoring above threshold on any scale, 48%). Demographic variables accounted for <1% of the variance of depression status, with vulnerabilities accounting for significantly more (pseudo R² = 0.16, χ²(change) = 150.9, df = 4, p < 0.001). Disease indices accounted for 7% of the variance in depression (pseudo R² = 0.07, χ² = 137.9, p < 0.001). However, adding the vulnerabilities increased the overall variance explained to 22% (pseudo R² = 0.22, χ² = 58.6, df = 4, p < 0.001). Theoretical vulnerabilities predicted depression status better than did either demographic or disease indices. The presence of these proximal causes of depression suggests that depression in ACS patients is not simply a result of cardiovascular disease severity.

Prediction-error variance in Bayesian model updating: a comparative study

NASA Astrophysics Data System (ADS)

Asadollahi, Parisa; Li, Jian; Huang, Yong

2017-04-01

In Bayesian model updating, the likelihood function is commonly formulated by stochastic embedding in which the maximum information entropy probability model of prediction error variances plays an important role and it is Gaussian distribution subject to the first two moments as constraints. The selection of prediction error variances can be formulated as a model class selection problem, which automatically involves a trade-off between the average data-fit of the model class and the information it extracts from the data. Therefore, it is critical for the robustness in the updating of the structural model especially in the presence of modeling errors. To date, three ways of considering prediction error variances have been seem in the literature: 1) setting constant values empirically, 2) estimating them based on the goodness-of-fit of the measured data, and 3) updating them as uncertain parameters by applying Bayes' Theorem at the model class level. In this paper, the effect of different strategies to deal with the prediction error variances on the model updating performance is investigated explicitly. A six-story shear building model with six uncertain stiffness parameters is employed as an illustrative example. Transitional Markov Chain Monte Carlo is used to draw samples of the posterior probability density function of the structure model parameters as well as the uncertain prediction variances. The different levels of modeling uncertainty and complexity are modeled through three FE models, including a true model, a model with more complexity, and a model with modeling error. Bayesian updating is performed for the three FE models considering the three aforementioned treatments of the prediction error variances. The effect of number of measurements on the model updating performance is also examined in the study. The results are compared based on model class assessment and indicate that updating the prediction error variances as uncertain parameters at the model class level produces more robust results especially when the number of measurement is small.

[Fire behavior of Mongolian oak leaves fuel bed under no-wind and zero-slope conditions. II. Analysis of the factors affecting flame length and residence time and related prediction models].

PubMed

Zhang, Ji-Li; Liu, Bo-Fei; Di, Xue-Ying; Chu, Teng-Fei; Jin, Sen

2012-11-01

Taking fuel moisture content, fuel loading, and fuel bed depth as controlling factors, the fuel beds of Mongolian oak leaves in Maoershan region of Northeast China in field were simulated, and a total of one hundred experimental burnings under no-wind and zero-slope conditions were conducted in laboratory, with the effects of the fuel moisture content, fuel loading, and fuel bed depth on the flame length and its residence time analyzed and the multivariate linear prediction models constructed. The results indicated that fuel moisture content had a significant negative liner correlation with flame length, but less correlation with flame residence time. Both the fuel loading and the fuel bed depth were significantly positively correlated with flame length and its residence time. The interactions of fuel bed depth with fuel moisture content and fuel loading had significant effects on the flame length, while the interactions of fuel moisture content with fuel loading and fuel bed depth affected the flame residence time significantly. The prediction model of flame length had better prediction effect, which could explain 83.3% of variance, with a mean absolute error of 7.8 cm and a mean relative error of 16.2%, while the prediction model of flame residence time was not good enough, which could only explain 54% of variance, with a mean absolute error of 9.2 s and a mean relative error of 18.6%.

Validity of Futrex-5000 for body composition determination.

PubMed

McLean, K P; Skinner, J S

1992-02-01

Underwater weighing (UWW), skinfolds (SKF), and the Futrex-5000 (FTX) were compared by using UWW as the criterion measure of body fat in 30 male and 31 female Caucasians. Estimates of body fat (% fat) were obtained using The Y's Way to Fitness SKF equations and the standard FTX technique with near-infrared interactance (NIR) measured at the biceps, plus six sites for men and five sites for women. SKF correlated significantly higher with UWW than did FTX with UWW for males (0.95 vs 0.80), females (0.88 vs 0.63), and the whole group (0.94 vs 0.81). Fewer subjects (52%) were within +/- 4% of the UWW value using FTX, compared with 87% with SKF. FTX overestimated body fat in lean subjects with less than 8% fat and underestimated it in subjects with greater than 30% fat. Measuring NIR at additional sites did not improve the predicted variance. Partial F-tests indicate that using body mass index, instead of height and weight, in the FTX equation improved body fat prediction for females. Biceps NIR predicted additional variance in body fat beyond height, weight, frame size, and activity level but little variance above that predicted by these four variables plus SKF (2% more in males and less than 1% in females). Thus, SKF give more information and more accurately predict body fat, especially at the extremes of the body fat continuum.

Auditory brainstem response to complex sounds predicts self-reported speech-in-noise performance.

PubMed

Anderson, Samira; Parbery-Clark, Alexandra; White-Schwoch, Travis; Kraus, Nina

2013-02-01

To compare the ability of the auditory brainstem response to complex sounds (cABR) to predict subjective ratings of speech understanding in noise on the Speech, Spatial, and Qualities of Hearing Scale (SSQ; Gatehouse & Noble, 2004) relative to the predictive ability of the Quick Speech-in-Noise test (QuickSIN; Killion, Niquette, Gudmundsen, Revit, & Banerjee, 2004) and pure-tone hearing thresholds. Participants included 111 middle- to older-age adults (range = 45-78) with audiometric configurations ranging from normal hearing levels to moderate sensorineural hearing loss. In addition to using audiometric testing, the authors also used such evaluation measures as the QuickSIN, the SSQ, and the cABR. Multiple linear regression analysis indicated that the inclusion of brainstem variables in a model with QuickSIN, hearing thresholds, and age accounted for 30% of the variance in the Speech subtest of the SSQ, compared with significantly less variance (19%) when brainstem variables were not included. The authors' results demonstrate the cABR's efficacy for predicting self-reported speech-in-noise perception difficulties. The fact that the cABR predicts more variance in self-reported speech-in-noise (SIN) perception than either the QuickSIN or hearing thresholds indicates that the cABR provides additional insight into an individual's ability to hear in background noise. In addition, the findings underscore the link between the cABR and hearing in noise.

Hierarchical Bayesian Model Averaging for Chance Constrained Remediation Designs

NASA Astrophysics Data System (ADS)

Chitsazan, N.; Tsai, F. T.

2012-12-01

Groundwater remediation designs are heavily relying on simulation models which are subjected to various sources of uncertainty in their predictions. To develop a robust remediation design, it is crucial to understand the effect of uncertainty sources. In this research, we introduce a hierarchical Bayesian model averaging (HBMA) framework to segregate and prioritize sources of uncertainty in a multi-layer frame, where each layer targets a source of uncertainty. The HBMA framework provides an insight to uncertainty priorities and propagation. In addition, HBMA allows evaluating model weights in different hierarchy levels and assessing the relative importance of models in each level. To account for uncertainty, we employ a chance constrained (CC) programming for stochastic remediation design. Chance constrained programming was implemented traditionally to account for parameter uncertainty. Recently, many studies suggested that model structure uncertainty is not negligible compared to parameter uncertainty. Using chance constrained programming along with HBMA can provide a rigorous tool for groundwater remediation designs under uncertainty. In this research, the HBMA-CC was applied to a remediation design in a synthetic aquifer. The design was to develop a scavenger well approach to mitigate saltwater intrusion toward production wells. HBMA was employed to assess uncertainties from model structure, parameter estimation and kriging interpolation. An improved harmony search optimization method was used to find the optimal location of the scavenger well. We evaluated prediction variances of chloride concentration at the production wells through the HBMA framework. The results showed that choosing the single best model may lead to a significant error in evaluating prediction variances for two reasons. First, considering the single best model, variances that stem from uncertainty in the model structure will be ignored. Second, considering the best model with non-dominant model weight may underestimate or overestimate prediction variances by ignoring other plausible propositions. Chance constraints allow developing a remediation design with a desirable reliability. However, considering the single best model, the calculated reliability will be different from the desirable reliability. We calculated the reliability of the design for the models at different levels of HBMA. The results showed that by moving toward the top layers of HBMA, the calculated reliability converges to the chosen reliability. We employed the chance constrained optimization along with the HBMA framework to find the optimal location and pumpage for the scavenger well. The results showed that using models at different levels in the HBMA framework, the optimal location of the scavenger well remained the same, but the optimal extraction rate was altered. Thus, we concluded that the optimal pumping rate was sensitive to the prediction variance. Also, the prediction variance was changed by using different extraction rate. Using very high extraction rate will cause prediction variances of chloride concentration at the production wells to approach zero regardless of which HBMA models used.

Predicting adolescents' disclosure of personal information in exchange for commercial incentives: an application of an extended theory of planned behavior.

PubMed

Heirman, Wannes; Walrave, Michel; Ponnet, Koen

2013-02-01

This study adopts a global theoretical framework to predict adolescents' disclosure of personal information in exchange for incentives offered by commercial Websites. The study postulates and tests the validity of a model based on the theory of planned behavior (TPB), including antecedent factors of attitude and perceived behavioral control (PBC). A survey was conducted among 1,042 respondents. Results from SEM analyses show that the hypothesized model fits the empirical data well. The model accounts for 61.9 percent of the variance in adolescents' intention to disclose and 43.7 percent of the variance in self-reported disclosure. Perceived social pressure exerted by significant others (subjective norm) is the most important TPB factor in predicting intention to disclose personal information in exchange for incentives. This finding suggests that in discussions of adolescents' information privacy, the importance of social factors outweighs the individually oriented TPB factors of attitude and PBC. Moreover, privacy concern and trust propensity are significant predictors of respondents' attitudes toward online disclosure in exchange for commercial incentives, whereas the frequency of Internet use significantly affects their level of PBC.

Predictors of men's sexual response to erotic film stimuli: the role of affect and self-reported thoughts.

PubMed

Oliveira, Cátia; Laja, Pedro; Carvalho, Joana; Quinta Gomes, Ana; Vilarinho, Sandra; Janssen, Erick; Nobre, Pedro J

2014-11-01

Both emotions and cognitions seem to play a role in determining sexual arousal. However, no studies to date have tested the effects of self-reported thoughts on subjective sexual arousal and genital response using psychophysiological methods. The aim of the present study was to evaluate the role of self-reported thoughts and affect during exposure to erotic material in predicting subjective and genital responses in sexually healthy men. Twenty-seven men were presented with two explicit films, and genital responses, subjective sexual arousal, self-reported thoughts, and positive and negative affect were assessed. Men's genital responses, subjective sexual arousal, affective responses, and self-reported thoughts during exposure to sexual stimulus were measured. Regression analyses revealed that genital responses were predicted by self-reported thoughts (explaining 20% of the variance) but not by affect during exposure to erotic films. On the other hand, subjective sexual arousal was significantly predicted by both positive and negative affect (explaining 18% of the variance) and self-reported thoughts (explaining 37% of the variance). Follow-up analyses using the single predictors showed that "sexual arousal thoughts" were the only significant predictor of subjective response (β = 0.64; P < 0.01) and that "distracting/disengaging thoughts" were the best predictor of genital response (β = -0.51; P < 0.05). The findings of this study suggest that both affect and sexual arousal thoughts play an important role in men's subjective sexual response, whereas genital response seems to be better predicted by distracting thoughts. © 2014 International Society for Sexual Medicine.

Attitudes and exercise adherence: test of the Theories of Reasoned Action and Planned Behaviour.

PubMed

Smith, R A; Biddle, S J

1999-04-01

Three studies of exercise adherence and attitudes are reported that tested the Theory of Reasoned Action and the Theory of Planned Behaviour. In a prospective study of adherence to a private fitness club, structural equation modelling path analysis showed that attitudinal and social normative components of the Theory of Reasoned Action accounted for 13.1% of the variance in adherence 4 months later, although only social norm significantly predicted intention. In a second study, the Theory of Planned Behaviour was used to predict both physical activity and sedentary behaviour. Path analyses showed that attitude and perceived control, but not social norm, predicted total physical activity. Physical activity was predicted from intentions and control over sedentary behaviour. Finally, an intervention study with previously sedentary adults showed that intentions to be active measured at the start and end of a 10-week intervention were associated with the planned behaviour variables. A multivariate analysis of variance revealed no significant multivariate effects for time on the planned behaviour variables measured before and after intervention. Qualitative data provided evidence that participants had a positive experience on the intervention programme and supported the role of social normative factors in the adherence process.

Investigating the predictive validity of implicit and explicit measures of motivation in problem-solving behavioural tasks.

PubMed

Keatley, David; Clarke, David D; Hagger, Martin S

2013-09-01

Research into the effects of individuals'autonomous motivation on behaviour has traditionally adopted explicit measures and self-reported outcome assessment. Recently, there has been increased interest in the effects of implicit motivational processes underlying behaviour from a self-determination theory (SDT) perspective. The aim of the present research was to provide support for the predictive validity of an implicit measure of autonomous motivation on behavioural persistence on two objectively measurable tasks. SDT and a dual-systems model were adopted as frameworks to explain the unique effects offered by explicit and implicit autonomous motivational constructs on behavioural persistence. In both studies, implicit autonomous motivation significantly predicted unique variance in time spent on each task. Several explicit measures of autonomous motivation also significantly predicted persistence. Results provide support for the proposed model and the inclusion of implicit measures in research on motivated behaviour. In addition, implicit measures of autonomous motivation appear to be better suited to explaining variance in behaviours that are more spontaneous or unplanned. Future implications for research examining implicit motivation from dual-systems models and SDT approaches are outlined. © 2012 The British Psychological Society.

Strategies for Selecting Crosses Using Genomic Prediction in Two Wheat Breeding Programs.

PubMed

Lado, Bettina; Battenfield, Sarah; Guzmán, Carlos; Quincke, Martín; Singh, Ravi P; Dreisigacker, Susanne; Peña, R Javier; Fritz, Allan; Silva, Paula; Poland, Jesse; Gutiérrez, Lucía

2017-07-01

The single most important decision in plant breeding programs is the selection of appropriate crosses. The ideal cross would provide superior predicted progeny performance and enough diversity to maintain genetic gain. The aim of this study was to compare the best crosses predicted using combinations of mid-parent value and variance prediction accounting for linkage disequilibrium (V) or assuming linkage equilibrium (V). After predicting the mean and the variance of each cross, we selected crosses based on mid-parent value, the top 10% of the progeny, and weighted mean and variance within progenies for grain yield, grain protein content, mixing time, and loaf volume in two applied wheat ( L.) breeding programs: Instituto Nacional de Investigación Agropecuaria (INIA) Uruguay and CIMMYT Mexico. Although the variance of the progeny is important to increase the chances of finding superior individuals from transgressive segregation, we observed that the mid-parent values of the crosses drove the genetic gain but the variance of the progeny had a small impact on genetic gain for grain yield. However, the relative importance of the variance of the progeny was larger for quality traits. Overall, the genomic resources and the statistical models are now available to plant breeders to predict both the performance of breeding lines per se as well as the value of progeny from any potential crosses. Copyright © 2017 Crop Science Society of America.

Cognitive predictors of everyday functioning in older adults: results from the ACTIVE Cognitive Intervention Trial.

PubMed

Gross, Alden L; Rebok, George W; Unverzagt, Frederick W; Willis, Sherry L; Brandt, Jason

2011-09-01

The present study sought to predict changes in everyday functioning using cognitive tests. Data from the Advanced Cognitive Training for Independent and Vital Elderly trial were used to examine the extent to which competence in different cognitive domains--memory, inductive reasoning, processing speed, and global mental status--predicts prospectively measured everyday functioning among older adults. Coefficients of determination for baseline levels and trajectories of everyday functioning were estimated using parallel process latent growth models. Each cognitive domain independently predicts a significant proportion of the variance in baseline and trajectory change of everyday functioning, with inductive reasoning explaining the most variance (R2 = .175) in baseline functioning and memory explaining the most variance (R2 = .057) in changes in everyday functioning. Inductive reasoning is an important determinant of current everyday functioning in community-dwelling older adults, suggesting that successful performance in daily tasks is critically dependent on executive cognitive function. On the other hand, baseline memory function is more important in determining change over time in everyday functioning, suggesting that some participants with low baseline memory function may reflect a subgroup with incipient progressive neurologic disease.

Prediction possibilities of Arosa total ozone

NASA Astrophysics Data System (ADS)

Kane, R. P.

1987-01-01

Using the periodicities obtained by a Maximum Entropy Spectral Analysis (MESA) of the Arosa total ozone data ( CC') series for 1932 1971, the values predicted for 1972 onwards were compared with the observed values of the ( AD) series. A change of level was noticed, with the observed ( AD) values lower by about 7 D.U. Also, the matching was poor in 1980, 1981, 1982. In the monthly values, the most prominent periodicity was the annual wave, comprising some 80% variance. In the 12 month running averages, the annual wave was eliminated and the most prominent periodicity was T=3.7 years, encompassing roundly 20% variance. This and other periodicities at T=4.7, 5.4, 6.2, 10 and 16 years were all statistically significant at a 3.5δ a priori i.e., 2δ a posteriori level. However, the predictions from these were unsatisfactory, probably because some of these periodicities may be transient i.e., changing amplitudes and/or phases with time. Thus, no meaningful prediction seem possible for Arosa total ozone.

Vicarious resilience in sexual assault and domestic violence advocates.

PubMed

Frey, Lisa L; Beesley, Denise; Abbott, Deah; Kendrick, Elizabeth

2017-01-01

There is little research related to sexual assault and domestic violence advocates' experiences, with the bulk of the literature focused on stressors and systemic barriers that negatively impact efforts to assist survivors. However, advocates participating in these studies have also emphasized the positive impact they experience consequent to their work. This study explores the positive impact. Vicarious resilience, personal trauma experiences, peer relational quality, and perceived organizational support in advocates (n = 222) are examined. Also, overlap among the conceptual components of vicarious resilience is explored. The first set of multiple regressions showed that personal trauma experiences and peer relational health predicted compassion satisfaction and vicarious posttraumatic growth, with organizational support predicting only compassion satisfaction. The second set of multiple regressions showed that (a) there was significant shared variance between vicarious posttraumatic growth and compassion satisfaction; (b) after accounting for vicarious posttraumatic growth, organizational support accounted for significant variance in compassion satisfaction; and (c) after accounting for compassion satisfaction, peer relational health accounted for significant variance in vicarious posttraumatic growth. Results suggest that it may be more meaningful to conceptualize advocates' personal growth related to their work through the lens of a multidimensional construct such as vicarious resilience. Organizational strategies promoting vicarious resilience (e.g., shared organizational power, training components) are offered, and the value to trauma-informed care of fostering advocates' vicarious resilience is discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Typical intellectual engagement and cognition in the ninth decade of life: The Lothian Birth Cohort 1921.

PubMed

von Stumm, Sophie; Deary, Ian J

2012-09-01

Investment traits--the tendency to seek out and engage in cognitive activity--might affect intellectual growth across the life span, specifically the development from fluid to crystallized intelligence. Here we explore how childhood IQ at age 11 years, IQ at age 79, and the investment trait Typical Intellectual Engagement (TIE) at age 81 affect the mean level and change in verbal fluency scores, used as an indicator of crystallized intelligence, across the ages 79, 83, and 87 in the Lothian Birth Cohort 1921 (maximum N = 569; Deary, Whiteman, Starr, Whalley, & Fox, 2004). A first latent growth model showed significant variance in the mean level of verbal fluency and significant decline in verbal fluency from age 79 to age 87. The rate of change was invariant across study participants in the Lothian Birth Cohort 1921. A second model found that IQ at age 11 significantly predicted IQ at age 79 (β = .66; p < .001), which in turn predicted verbal fluency and TIE in the ninth decade of life with standardized path parameters of .46 and .15 (p < .001), respectively. TIE had a significant association with verbal fluency (β = .14, p = .002); together, IQ at age 11 and 79 and TIE accounted for 25.5% of the variance in verbal fluency. A final model identified the TIE subfactor of intellectual curiosity as a significant mediator of the effect of IQ on verbal fluency; the TIE subfactors abstract thinking, reading, and problem solving showed no significant associations. In summary, TIE--in particular, intellectual curiosity--significantly mediated the effects of IQ on crystallized intelligence in old age. Because there was no significant between-subjects variance in verbal fluency trajectories in the current study, neither TIE nor IQ were associated with individual differences in cognitive decline.

Prediction of specific depressive symptom clusters in youth with epilepsy: The NDDI-E-Y versus Neuro-QOL SF.

PubMed

Kellermann, Tanja S; Mueller, Martina; Carter, Emma G; Brooks, Byron; Smith, Gigi; Kopp, Olivia J; Wagner, Janelle L

2017-08-01

Proper assessment and early identification of depressive symptoms are essential to initiate treatment and minimize the risk for poor outcomes in youth with epilepsy (YWE). The current study examined the predictive utility of the Neurological Disorders Depression Inventory-Epilepsy for Youth (NDDI-E-Y) and the Neuro-QOL Depression Short Form (Neuro-QOL SF) in explaining variance in overall depressive symptoms and specific symptom clusters on the gold standard Children's Depression Inventory-2 (CDI-2). Cross-sectional study examining 99 YWE (female 68, mean age 14.7 years) during a routine epilepsy visit, who completed self-report measures of depressive symptoms, including the NDDI-E-Y, CDI-2, and the Neuro-QOL SF. Caregivers completed a measure of seizure severity. All sociodemographic and medical information was evaluated through electronic medical record review. After accounting for seizure and demographic variables, the NDDI-E-Y accounted for 45% of the variance in the CDI-2 Total score and the CDI-2 Ineffectiveness subscale. Furthermore, the NDDI-E-Y predicted CDI-2 Total scores and subscales similarly, with the exception of explaining significantly more variance in the CDI-2 Ineffectiveness subscale compared to the Negative Mood subscale. The NDDI-E-Y explained greater variance compared to Neuro-QOL SF across the Total (48% vs. 37%) and all CDI-2 subscale scores; however, the NDDI-E-Y emerged as a stronger predictor of only CDI-2 Ineffectiveness. Both the NDDI-E-Y and Neuro-QOL SF accounted for the lowest amount of variance in CDI-2 Negative Mood. Sensitivity was poor for the Neuro-QOL SF in predicting high versus low CDI-2 scores. The NDDI-E-Y has strong psychometrics and can be easily integrated into routine epilepsy care for quick, brief screening of depressive symptoms in YWE. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Prediction of Student Performance in Academic and Military Learning Environment: Use of Multiple Linear Regression Predictive Model and Hypothesis Testing

ERIC Educational Resources Information Center

Khan, Wasi Z.; Al Zubaidy, Sarim

2017-01-01

The variance in students' academic performance in a civilian institute and in a military technological institute could be linked to the environment of the competition available to the students. The magnitude of talent, domain of skills and volume of efforts students put are identical in both type of institutes. The significant factor is the…

Regulation of Motivation: Predicting Students' Homework Motivation Management at the Secondary School Level

ERIC Educational Resources Information Center

Xu, Jianzhong

2014-01-01

This study examines models of variables posited to predict students' homework motivation management (HMM), based on survey data from 866 8th graders (61 classes) and 745 11th graders (46 classes) in the south-eastern USA. Most of the variance in HMM occurred at the student level, with parent education as the only significant predictor at the class…

Host Genome Influence on Gut Microbial Composition and Microbial Prediction of Complex Traits in Pigs.

PubMed

Camarinha-Silva, Amelia; Maushammer, Maria; Wellmann, Robin; Vital, Marius; Preuss, Siegfried; Bennewitz, Jörn

2017-07-01

The aim of the present study was to analyze the interplay between gastrointestinal tract (GIT) microbiota, host genetics, and complex traits in pigs using extended quantitative-genetic methods. The study design consisted of 207 pigs that were housed and slaughtered under standardized conditions, and phenotyped for daily gain, feed intake, and feed conversion rate. The pigs were genotyped with a standard 60 K SNP chip. The GIT microbiota composition was analyzed by 16S rRNA gene amplicon sequencing technology. Eight from 49 investigated bacteria genera showed a significant narrow sense host heritability, ranging from 0.32 to 0.57. Microbial mixed linear models were applied to estimate the microbiota variance for each complex trait. The fraction of phenotypic variance explained by the microbial variance was 0.28, 0.21, and 0.16 for daily gain, feed conversion, and feed intake, respectively. The SNP data and the microbiota composition were used to predict the complex traits using genomic best linear unbiased prediction (G-BLUP) and microbial best linear unbiased prediction (M-BLUP) methods, respectively. The prediction accuracies of G-BLUP were 0.35, 0.23, and 0.20 for daily gain, feed conversion, and feed intake, respectively. The corresponding prediction accuracies of M-BLUP were 0.41, 0.33, and 0.33. Thus, in addition to SNP data, microbiota abundances are an informative source of complex trait predictions. Since the pig is a well-suited animal for modeling the human digestive tract, M-BLUP, in addition to G-BLUP, might be beneficial for predicting human predispositions to some diseases, and, consequently, for preventative and personalized medicine. Copyright © 2017 by the Genetics Society of America.

Investigating the Interaction Between Sleep Symptoms of Arousal and Acquired Capability in Predicting Suicidality.

PubMed

Hochard, Kevin D; Heym, Nadja; Townsend, Ellen

2017-06-01

Heightened arousal significantly interacts with acquired capability to predict suicidality. We explore this interaction with insomnia and nightmares independently of waking state arousal symptoms, and test predictions of the Interpersonal Theory of Suicide (IPTS) and Escape Theory in relation to these sleep arousal symptoms. Findings from our e-survey (n = 540) supported the IPTS over models of Suicide as Escape. Sleep-specific measurements of arousal (insomnia and nightmares) showed no main effect, yet interacted with acquired capability to predict increased suicidality. The explained variance in suicidality by the interaction (1%-2%) using sleep-specific measures was comparable to variance explained by interactions previously reported in the literature using measurements composed of a mix of waking and sleep state arousal symptoms. Similarly, when entrapment (inability to escape) was included in models, main effects of sleep symptoms arousal were not detected yet interacted with entrapment to predict suicidality. We discuss findings in relation to treatment options suggesting that sleep-specific interventions be considered for the long-term management of at-risk individuals. © 2016 The American Association of Suicidology.

Teacher Judgments of Classroom Behavior of Negro and White School Beginners.

ERIC Educational Resources Information Center

Long, Barbara H.; Henderson, Edmund H.

After six weeks of school, classroom teachers rated 95 Negro and 93 white first graders on 24 behavior scales. Mean total ratings did not differentiate the two groups, but variance was significantly higher for the whites. Total ratings predicted promotion for the Negroes, and for both groups were significantly (a) higher for the girls, (b)…

Variance in predicted cup size by 2-dimensional vs 3-dimensional computerized tomography-based templating in primary total hip arthroplasty.

PubMed

Osmani, Feroz A; Thakkar, Savyasachi; Ramme, Austin; Elbuluk, Ameer; Wojack, Paul; Vigdorchik, Jonathan M

2017-12-01

Preoperative total hip arthroplasty templating can be performed with radiographs using acetate prints, digital viewing software, or with computed tomography (CT) images. Our hypothesis is that 3D templating is more precise and accurate with cup size prediction as compared to 2D templating with acetate prints and digital templating software. Data collected from 45 patients undergoing robotic-assisted total hip arthroplasty compared cup sizes templated on acetate prints and OrthoView software to MAKOplasty software that uses CT scan. Kappa analysis determined strength of agreement between each templating modality and the final size used. t tests compared mean cup-size variance from the final size for each templating technique. Interclass correlation coefficient (ICC) determined reliability of digital and acetate planning by comparing predictions of the operating surgeon and a blinded adult reconstructive fellow. The Kappa values for CT-guided, digital, and acetate templating with the final size was 0.974, 0.233, and 0.262, respectively. Both digital and acetate templating significantly overpredicted cup size, compared to CT-guided methods ( P < .001). There was no significant difference between digital and acetate templating ( P  = .117). Interclass correlation coefficient value for digital and acetate templating was 0.928 and 0.931, respectively. CT-guided planning more accurately predicts hip implant cup size when compared to the significant overpredictions of digital and acetate templating. CT-guided templating may also lead to better outcomes due to bone stock preservation from a smaller and more accurate cup size predicted than that of digital and acetate predictions.

A time dependent mixing model to close PDF equations for transport in heterogeneous aquifers

NASA Astrophysics Data System (ADS)

Schüler, L.; Suciu, N.; Knabner, P.; Attinger, S.

2016-10-01

Probability density function (PDF) methods are a promising alternative to predicting the transport of solutes in groundwater under uncertainty. They make it possible to derive the evolution equations of the mean concentration and the concentration variance, used in moment methods. The mixing model, describing the transport of the PDF in concentration space, is essential for both methods. Finding a satisfactory mixing model is still an open question and due to the rather elaborate PDF methods, a difficult undertaking. Both the PDF equation and the concentration variance equation depend on the same mixing model. This connection is used to find and test an improved mixing model for the much easier to handle concentration variance. Subsequently, this mixing model is transferred to the PDF equation and tested. The newly proposed mixing model yields significantly improved results for both variance modelling and PDF modelling.

Social cognitive predictors of first- and non-first-generation college students' academic and life satisfaction.

PubMed

Garriott, Patton O; Hudyma, Aaron; Keene, Chesleigh; Santiago, Dana

2015-04-01

The present study tested Lent's (2004) social-cognitive model of normative well-being in a sample (N = 414) of first- and non-first-generation college students. A model depicting relationships between: positive affect, environmental supports, college self-efficacy, college outcome expectations, academic progress, academic satisfaction, and life satisfaction was examined using structural equation modeling. The moderating roles of perceived importance of attending college and intrinsic goal motivation were also explored. Results suggested the hypothesized model provided an adequate fit to the data while hypothesized relationships in the model were partially supported. Environmental supports predicted college self-efficacy, college outcome expectations, and academic satisfaction. Furthermore, college self-efficacy predicted academic progress while college outcome expectations predicted academic satisfaction. Academic satisfaction, but not academic progress predicted life satisfaction. The structural model explained 44% of the variance in academic progress, 56% of the variance in academic satisfaction, and 28% of the variance in life satisfaction. Mediation analyses indicated several significant indirect effects between variables in the model while moderation analyses revealed a 3-way interaction between academic satisfaction, intrinsic motivation for attending college, and first-generation college student status on life satisfaction. Results are discussed in terms of applying the normative model of well-being to promote first- and non-first-generation college students' academic and life satisfaction. (c) 2015 APA, all rights reserved).

The effect of thermal variance on the phenotype of marine turtle offspring.

PubMed

Horne, C R; Fuller, W J; Godley, B J; Rhodes, K A; Snape, R; Stokes, K L; Broderick, A C

2014-01-01

Temperature can have a profound effect on the phenotype of reptilian offspring, yet the bulk of current research considers the effects of constant incubation temperatures on offspring morphology, with few studies examining the natural thermal variance that occurs in the wild. Over two consecutive nesting seasons, we placed temperature data loggers in 57 naturally incubating clutches of loggerhead sea turtles Caretta caretta and found that greater diel thermal variance during incubation significantly reduced offspring mass, potentially reducing survival of hatchlings during their journey from the nest to offshore waters and beyond. With predicted scenarios of climate change, behavioral plasticity in nest site selection may be key for the survival of ectothermic species, particularly those with temperature-dependent sex determination.

Assessing Multivariate Constraints to Evolution across Ten Long-Term Avian Studies

PubMed Central

Teplitsky, Celine; Tarka, Maja; Møller, Anders P.; Nakagawa, Shinichi; Balbontín, Javier; Burke, Terry A.; Doutrelant, Claire; Gregoire, Arnaud; Hansson, Bengt; Hasselquist, Dennis; Gustafsson, Lars; de Lope, Florentino; Marzal, Alfonso; Mills, James A.; Wheelwright, Nathaniel T.; Yarrall, John W.; Charmantier, Anne

2014-01-01

Background In a rapidly changing world, it is of fundamental importance to understand processes constraining or facilitating adaptation through microevolution. As different traits of an organism covary, genetic correlations are expected to affect evolutionary trajectories. However, only limited empirical data are available. Methodology/Principal Findings We investigate the extent to which multivariate constraints affect the rate of adaptation, focusing on four morphological traits often shown to harbour large amounts of genetic variance and considered to be subject to limited evolutionary constraints. Our data set includes unique long-term data for seven bird species and a total of 10 populations. We estimate population-specific matrices of genetic correlations and multivariate selection coefficients to predict evolutionary responses to selection. Using Bayesian methods that facilitate the propagation of errors in estimates, we compare (1) the rate of adaptation based on predicted response to selection when including genetic correlations with predictions from models where these genetic correlations were set to zero and (2) the multivariate evolvability in the direction of current selection to the average evolvability in random directions of the phenotypic space. We show that genetic correlations on average decrease the predicted rate of adaptation by 28%. Multivariate evolvability in the direction of current selection was systematically lower than average evolvability in random directions of space. These significant reductions in the rate of adaptation and reduced evolvability were due to a general nonalignment of selection and genetic variance, notably orthogonality of directional selection with the size axis along which most (60%) of the genetic variance is found. Conclusions These results suggest that genetic correlations can impose significant constraints on the evolution of avian morphology in wild populations. This could have important impacts on evolutionary dynamics and hence population persistence in the face of rapid environmental change. PMID:24608111

Effects of field plot size on prediction accuracy of aboveground biomass in airborne laser scanning-assisted inventories in tropical rain forests of Tanzania.

PubMed

Mauya, Ernest William; Hansen, Endre Hofstad; Gobakken, Terje; Bollandsås, Ole Martin; Malimbwi, Rogers Ernest; Næsset, Erik

2015-12-01

Airborne laser scanning (ALS) has recently emerged as a promising tool to acquire auxiliary information for improving aboveground biomass (AGB) estimation in sample-based forest inventories. Under design-based and model-assisted inferential frameworks, the estimation relies on a model that relates the auxiliary ALS metrics to AGB estimated on ground plots. The size of the field plots has been identified as one source of model uncertainty because of the so-called boundary effects which increases with decreasing plot size. Recent research in tropical forests has aimed to quantify the boundary effects on model prediction accuracy, but evidence of the consequences for the final AGB estimates is lacking. In this study we analyzed the effect of field plot size on model prediction accuracy and its implication when used in a model-assisted inferential framework. The results showed that the prediction accuracy of the model improved as the plot size increased. The adjusted R 2 increased from 0.35 to 0.74 while the relative root mean square error decreased from 63.6 to 29.2%. Indicators of boundary effects were identified and confirmed to have significant effects on the model residuals. Variance estimates of model-assisted mean AGB relative to corresponding variance estimates of pure field-based AGB, decreased with increasing plot size in the range from 200 to 3000 m 2 . The variance ratio of field-based estimates relative to model-assisted variance ranged from 1.7 to 7.7. This study showed that the relative improvement in precision of AGB estimation when increasing field-plot size, was greater for an ALS-assisted inventory compared to that of a pure field-based inventory.

The Relationship Between Domestic Partner Violence and Suicidal Behaviors in an Adult Community Sample: Examining Hope Agency and Pathways as Protective Factors.

PubMed

Chang, Edward C; Yu, Elizabeth A; Kahle, Emma R; Du, Yifeng; Chang, Olivia D; Jilani, Zunaira; Yu, Tina; Hirsch, Jameson K

2017-10-01

We examined an additive and interactive model involving domestic partner violence (DPV) and hope in accounting for suicidal behaviors in a sample of 98 community adults. Results showed that DPV accounted for a significant amount of variance in suicidal behaviors. Hope further augmented the prediction model and accounted for suicidal behaviors beyond DPV. Finally, we found that DPV significantly interacted with both dimensions of hope to further account for additional variance in suicidal behaviors above and beyond the independent effects of DPV and hope. Implications for the role of hope in the relationship between DPV and suicidal behaviors are discussed.

The Moderating Role of Physical Self-Perceptions in the Relationship Between Maturity Status and Physical Self-Worth.

PubMed

Cox, Anne E; Cole, Amy N; Laurson, Kelly

2016-06-01

We tested the moderating role of physical self-perceptions in the relationship between physical maturity and physical self-worth (PSW). Students in Grades 5 through 8 (N = 241; 57% females; Mage = 12.30 years) completed a questionnaire assessing physical self-perceptions (i.e., perceived sport competence, conditioning, strength, and body attractiveness), PSW, and maturity status. Hierarchical multiple regression was used to test interactions between maturity and physical self-perceptions predicting PSW separately for boys and girls. For girls, maturity level and physical self-perceptions explained significant variance, F(5, 131) = 73.44, p < .001, R(2) = .74, with interactions explaining a little extra variance, ΔF = 3.42, p = .01, ΔR(2) = .03. Perceived attractiveness interacted with maturity status to predict PSW (p = .01), indicating that maturity was positively related to PSW only for girls with higher body attractiveness. Maturity status and physical self-perceptions also significantly predicted PSW in boys, F(5, 98) = 46.52, p <  .001, R(2) = .70, with interactions explaining a little extra variance, ΔF = 3.16, p = .02, ΔR(2) = .04. A statistically significant interaction between perceived strength and maturity (p <  .001) indicated that maturity related positively to PSW, but only for boys with higher perceived strength. The maturity-PSW relationship differs by gender and depends partly on physical self-perceptions. This finding reinforces previous findings that illustrate the relative importance of perceived attractiveness and strength for girls and boys, respectively. PSW is an important predictor of physical activity behavior; therefore, it is critical to understand the interplay between these key antecedents.

Age, weight, and the front abdominal power test as predictors of isokinetic trunk strength and work in young men and women.

PubMed

Cowley, Patrick M; Fitzgerald, Sharon; Sottung, Kyle; Swensen, Thomas

2009-05-01

First we tested the reliability of two new field tests of core stability (plank to fatigue test [PFT] and front abdominal power test [FAPT]), as well as established measures of core stability (isokinetic trunk extension and flexion strength [TES and TFS] and work [TEW and TFW]) over 3 days in 8 young men and women (24.0 +/- 3.1 years). The TES, TFS, TFW, and FAPT were highly reliable, TEW was moderately reliable, and PFT were unreliable for use during a single testing session. Next, we determined if age, weight, and the data from the reliable field test (FAPT) were predictive of TES, TEW, TFS, and TFW in 50 young men and women (19.0 +/- 1.2 years). The FAPT was the only significant predictor of TES and TEW in young women, explaining 16 and 15% of the variance in trunk performance, respectively. Weight was the only significant predictor of TFS and TFW in young women, explaining 28 and 14% of the variance in trunk performance, respectively. In young men, weight was the only significant predictor of TES, TEW, TFS, and TFW, and explained 27, 35, 42, and 33%, respectively, of the variance in trunk performance. In conclusion, the ability of weight and the FAPT to predict TES, TEW, TFS, and TFW was more frequent in young men than women. Additionally, because the FAPT requires few pieces of equipment, is fast to administer, and predicts isokinetic TES and TEW in young women, it can be used to provide a field-based estimate of isokinetic TES and TEW in women without history of back or lower-extremity injury.

Obtaining Reliable Predictions of Terrestrial Energy Coupling From Real-Time Solar Wind Measurement

NASA Technical Reports Server (NTRS)

Weimer, Daniel R.

2001-01-01

The first draft of a manuscript titled "Variable time delays in the propagation of the interplanetary magnetic field" has been completed, for submission to the Journal of Geophysical Research. In the preparation of this manuscript all data and analysis programs had been updated to the highest temporal resolution possible, at 16 seconds or better. The program which computes the "measured" IMF propagation time delays from these data has also undergone another improvement. In another significant development, a technique has been developed in order to predict IMF phase plane orientations, and the resulting time delays, using only measurements from a single satellite at L1. The "minimum variance" method is used for this computation. Further work will be done on optimizing the choice of several parameters for the minimum variance calculation.

Population sexual behavior and HIV prevalence in Sub-Saharan Africa: missing links?

PubMed

Omori, Ryosuke; Abu-Raddad, Laith J

2016-03-01

Patterns of sexual partnering should shape HIV transmission in human populations. The objective of this study was to assess empirical associations between population casual sex behavior and HIV prevalence, and between different measures of casual sex behavior. An ecological study design was applied to nationally representative data, those of the Demographic and Health Surveys, in 25 countries of Sub-Saharan Africa. Spearman rank correlation was used to assess different correlations for males and females and their statistical significance. Correlations between HIV prevalence and means and variances of the number of casual sex partners were positive, but small and statistically insignificant. The majority of correlations across means and variances of the number of casual sex partners were positive, large, and statistically significant. However, all correlations between the means, as well as variances, and the variance of unmarried females were weak and statistically insignificant. Population sexual behavior was not predictive of HIV prevalence across these countries. Nevertheless, the strong correlations across means and variances of sexual behavior suggest that self-reported sexual data are self-consistent and convey valid information content. Unmarried female behavior seemed puzzling, but could be playing an influential role in HIV transmission patterns. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Do the same factors predict outcome in schizophrenia and non-schizophrenia syndromes after first-episode psychosis? A two-year follow-up study.

PubMed

Peña, Javier; Segarra, Rafael; Ojeda, Natalia; García, Jon; Eguiluz, José I; Gutiérrez, Miguel

2012-06-01

The aim of this two-year longitudinal study was to identify the best baseline predictors of functional outcome in first-episode psychosis (FEP). We tested whether the same factors predict functional outcomes in two different subsamples of FEP patients: schizophrenia and non-schizophrenia syndrome groups. Ninety-five patients with FEP underwent a full clinical evaluation (i.e., PANSS, Mania, Depression and Insight). Functional outcome measurements included the WHO Disability Assessment Schedule (DAS-WHO), Global Assessment of Functioning (GAF) and Clinical Global Impression (CGI). Estimation of cognition was obtained by a neuropsychological battery which included attention, processing speed, language, memory and executive functioning. Greater severity of visuospatial functioning at baseline predicted poorer functional outcome as measured by the three functional scales (GAF, CGI and DAS-WHO) in the pooled FEP sample (explaining ut to the 12%, 9% and 10% of the variance, respectively). Negative symptoms also effectively contributed to predict GAF scores (8%). However, we obtained different predictive values after differentiating sample diagnoses. Processing speed significantly predicted most functional outcome measures in patients with schizophrenia, whereas visuospatial functioning was the only significant predictor of functional outcomes in the non-schizophrenia subgroup. Our results suggest that processing speed, visuospatial functioning and negative symptoms significantly (but differentially) predict outcomes in patients with FEP, depending on their clinical progression. For patients without a schizophrenia diagnosis, visuospatial functioning was the best predictor of functional outcome. The performance on processing speed seemed to be a key factor in more severe syndromes. However, only a small proportion of the variance could be explained by the model, so there must be many other factors that have to be considered. Copyright © 2012 Elsevier Ltd. All rights reserved.

Models to predict emissions of health-damaging pollutants and global warming contributions of residential fuel/stove combinations in China.

PubMed

Edwards, Rufus D; Smith, Kirk R; Zhang, Junfeng; Ma, Yuqing

2003-01-01

Residential energy use in developing countries has traditionally been associated with combustion devices of poor energy efficiency, which have been shown to produce substantial health-damaging pollution, contributing significantly to the global burden of disease, and greenhouse gas (GHG) emissions. Precision of these estimates in China has been hampered by limited data on stove use and fuel consumption in residences. In addition limited information is available on variability of emissions of pollutants from different stove/fuel combinations in typical use, as measurement of emission factors requires measurement of multiple chemical species in complex burn cycle tests. Such measurements are too costly and time consuming for application in conjunction with national surveys. Emissions of most of the major health-damaging pollutants (HDP) and many of the gases that contribute to GHG emissions from cooking stoves are the result of the significant portion of fuel carbon that is diverted to products of incomplete combustion (PIC) as a result of poor combustion efficiencies. The approximately linear increase in emissions of PIC with decreasing combustion efficiencies allows development of linear models to predict emissions of GHG and HDP intrinsically linked to CO2 and PIC production, and ultimately allows the prediction of global warming contributions from residential stove emissions. A comprehensive emissions database of three burn cycles of 23 typical fuel/stove combinations tested in a simulated village house in China has been used to develop models to predict emissions of HDP and global warming commitment (GWC) from cooking stoves in China, that rely on simple survey information on stove and fuel use that may be incorporated into national surveys. Stepwise regression models predicted 66% of the variance in global warming commitment (CO2, CO, CH4, NOx, TNMHC) per 1 MJ delivered energy due to emissions from these stoves if survey information on fuel type was available. Subsequently if stove type is known, stepwise regression models predicted 73% of the variance. Integrated assessment of policies to change stove or fuel type requires that implications for environmental impacts, energy efficiency, global warming and human exposures to HDP emissions can be evaluated. Frequently, this involves measurement of TSP or CO as the major HDPs. Incorporation of this information into models to predict GWC predicted 79% and 78% of the variance respectively. Clearly, however, the complexity of making multiple measurements in conjunction with a national survey would be both expensive and time consuming. Thus, models to predict HDP using simple survey information, and with measurement of either CO/CO2 or TSP/CO2 to predict emission factors for the other HDP have been derived. Stepwise regression models predicted 65% of the variance in emissions of total suspended particulate as grams of carbon (TSPC) per 1 MJ delivered if survey information on fuel and stove type was available and 74% if the CO/CO2 ratio was measured. Similarly stepwise regression models predicted 76% of the variance in COC emissions per MJ delivered with survey information on stove and fuel type and 85% if the TSPC/CO2 ratio was measured. Ultimately, with international agreements on emissions trading frameworks, similar models based on extensive databases of the fate of fuel carbon during combustion from representative household stoves would provide a mechanism for computing greenhouse credits in the residential sector as part of clean development mechanism frameworks and monitoring compliance to control regimes.

Contrast model for three-dimensional vehicles in natural lighting and search performance analysis

NASA Astrophysics Data System (ADS)

Witus, Gary; Gerhart, Grant R.; Ellis, R. Darin

2001-09-01

Ground vehicles in natural lighting tend to have significant and systematic variation in luminance through the presented area. This arises, in large part, from the vehicle surfaces having different orientations and shadowing relative to the source of illumination and the position of the observer. These systematic differences create the appearance of a structured 3D object. The 3D appearance is an important factor in search, figure-ground segregation, and object recognition. We present a contrast metric to predict search and detection performance that accounts for the 3D structure. The approach first computes the contrast of the front (or rear), side, and top surfaces. The vehicle contrast metric is the area-weighted sum of the absolute values of the contrasts of the component surfaces. The 3D structure contrast metric, together with target height, account for more than 80% of the variance in probability of detection and 75% of the variance in search time. When false alarm effects are discounted, they account for 89% of the variance in probability of detection and 95% of the variance in search time. The predictive power of the signature metric, when calibrated to half the data and evaluated against the other half, is 90% of the explanatory power.

Utility functions predict variance and skewness risk preferences in monkeys

PubMed Central

Genest, Wilfried; Stauffer, William R.; Schultz, Wolfram

2016-01-01

Utility is the fundamental variable thought to underlie economic choices. In particular, utility functions are believed to reflect preferences toward risk, a key decision variable in many real-life situations. To assess the validity of utility representations, it is therefore important to examine risk preferences. In turn, this approach requires formal definitions of risk. A standard approach is to focus on the variance of reward distributions (variance-risk). In this study, we also examined a form of risk related to the skewness of reward distributions (skewness-risk). Thus, we tested the extent to which empirically derived utility functions predicted preferences for variance-risk and skewness-risk in macaques. The expected utilities calculated for various symmetrical and skewed gambles served to define formally the direction of stochastic dominance between gambles. In direct choices, the animals’ preferences followed both second-order (variance) and third-order (skewness) stochastic dominance. Specifically, for gambles with different variance but identical expected values (EVs), the monkeys preferred high-variance gambles at low EVs and low-variance gambles at high EVs; in gambles with different skewness but identical EVs and variances, the animals preferred positively over symmetrical and negatively skewed gambles in a strongly transitive fashion. Thus, the utility functions predicted the animals’ preferences for variance-risk and skewness-risk. Using these well-defined forms of risk, this study shows that monkeys’ choices conform to the internal reward valuations suggested by their utility functions. This result implies a representation of utility in monkeys that accounts for both variance-risk and skewness-risk preferences. PMID:27402743

Utility functions predict variance and skewness risk preferences in monkeys.

PubMed

Genest, Wilfried; Stauffer, William R; Schultz, Wolfram

2016-07-26

Utility is the fundamental variable thought to underlie economic choices. In particular, utility functions are believed to reflect preferences toward risk, a key decision variable in many real-life situations. To assess the validity of utility representations, it is therefore important to examine risk preferences. In turn, this approach requires formal definitions of risk. A standard approach is to focus on the variance of reward distributions (variance-risk). In this study, we also examined a form of risk related to the skewness of reward distributions (skewness-risk). Thus, we tested the extent to which empirically derived utility functions predicted preferences for variance-risk and skewness-risk in macaques. The expected utilities calculated for various symmetrical and skewed gambles served to define formally the direction of stochastic dominance between gambles. In direct choices, the animals' preferences followed both second-order (variance) and third-order (skewness) stochastic dominance. Specifically, for gambles with different variance but identical expected values (EVs), the monkeys preferred high-variance gambles at low EVs and low-variance gambles at high EVs; in gambles with different skewness but identical EVs and variances, the animals preferred positively over symmetrical and negatively skewed gambles in a strongly transitive fashion. Thus, the utility functions predicted the animals' preferences for variance-risk and skewness-risk. Using these well-defined forms of risk, this study shows that monkeys' choices conform to the internal reward valuations suggested by their utility functions. This result implies a representation of utility in monkeys that accounts for both variance-risk and skewness-risk preferences.

Clinical Assessment of Family Caregivers in Dementia.

ERIC Educational Resources Information Center

Rankin, Eric D.; And Others

1992-01-01

Evaluated development of integrated family assessment inventory based on Double ABCX and Circumplex models of family functioning and its clinical utility with 121 primary family caregivers from cognitive disorders program. Proposed model predicted significant proportion of variance associated with caregiver stress and strain. Several aspects of…

Predicting a 10 repetition maximum for the free weight parallel squat using the 45 degrees angled leg press.

PubMed

Willardson, Jeffrey M; Bressel, Eadric

2004-08-01

The purpose of this research was to devise prediction equations whereby a 10 repetition maximum (10RM) for the free weight parallel squat could be predicted using the following predictor variables: 10RM for the 45 degrees angled leg press, body mass, and limb length. Sixty men were tested over a 3-week period, with 1 testing session each week. During each testing session, subjects performed a 10RM for the free weight parallel squat and 45 degrees angled leg press. Stepwise multiple regression analysis showed leg press mass lifted to be a significant predictor of squat mass lifted for both the advanced and the novice groups (p < 0.05). Leg press mass lifted accounted for approximately 25% of the variance in squat mass lifted for the novice group and 55% of the variance in squat mass lifted for the advanced group. Limb length and body mass were not significant predictors of squat mass lifted for either group. The following prediction equations were devised: (a) novice group squat mass = leg press mass (0.210) + 36.244 kg, (b) advanced group squat mass = leg press mass (0.310) + 19.438 kg, and (c) subject pool squat mass = leg press mass (0.354) + 2.235 kg. These prediction equations may save time and reduce the risk of injury when switching from the leg press to the squat exercise.

Competitiveness facets and sensation seeking as predictors of problem gambling among a sample of university student gamblers.

PubMed

Harris, Nicholas; Newby, Jennifer; Klein, Rupert G

2015-06-01

Understanding the factors that contribute to problem gambling (PG) is imperative. Individual differences in sensation seeking (SS), as measured by the Sensation Seeking Scale Form (SSS-V), have been found to be predictive of PG among university student samples. However, what is less clear, is if the four SSS-V subscales capture unique facets of SS that are particularly predictive of PG. Much less studied than SS, competitiveness has also been found to be predictive of PG. The Competitiveness Orientation Measure (COM) is a newly developed measure of competitiveness, comprising of four facets. The main purpose of the current study was to examine if these four facets of competitiveness predicted variance in PG over and above the variance predicted by the four SSS-V subscales. Participants included 158 university student gamblers. Sequential regression analysis showed that after accounting for gender, age, and the four SSS-V subscales the only facet of the COM found to be a significant predictor of PG severity was Dominant Competitiveness. Dominant Competitiveness predicted an additional 11% of PG severity. These results provide support for the Dominant Competitiveness subscale of the COM as having utility in predicting PG over and above the predictive utility of the SSS-V subscales. Practical implications for the current findings are discussed.

Emotional Intelligence and Personality Traits as Predictors of Occupational Therapy students' Practice Education Performance: A Cross-Sectional Study.

PubMed

Brown, Ted; Williams, Brett; Etherington, Jamie

2016-12-01

This study investigated whether occupational therapy students' emotional intelligence and personality traits are predictive of specific aspects of their fieldwork performance. A total of 114 second and third year undergraduate occupational therapy students (86.6% response rate) completed the Genos Emotional Intelligence Inventory (Genos EI) and the Ten-Item Personality Inventory (TIPI). Fieldwork performance scores were obtained from the Student Practice Evaluation Form Revised (SPEF-R). Linear regressions were completed with the SPEF-R domains being the dependent variables and the Genos EI and TIPI factors being the independent variables. Regression analysis results revealed that the Genos EI subscales of Emotional Management of Others (EMO), Emotional Awareness of Others (EAO), Emotional Expression (EEX) and Emotional Reasoning (ERE) were significant predictors of various domains of students' fieldwork performance. EAO and ERE were significant predictors of students' Communication Skills accounting for 4.6% of its variance. EMO, EAO, EEX and ERE were significant predictors of students' Documentation Skills explaining 6.8% of its variance. EMO was a significant predictor of students' Professional Behaviour accounting for 3.2% of its variance. No TIPI factors were found to be significant predictors of the SPEF-R domains. Occupational therapy students' emotional intelligence was a significant predictor of components of their fieldwork performance while students' personality traits were not. The convenience sampling approach used, small sample size recruited and potential issue of social desirability of the self-reported Genos EI and TIPI data are acknowledged as study limitations. It is recommended that other studies be completed to investigate if any other relevant constructs or factors are predictive of occupational therapy students' fieldwork performance. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Variance in total levels of phospholipase C zeta (PLC-ζ) in human sperm may limit the applicability of quantitative immunofluorescent analysis as a diagnostic indicator of oocyte activation capability.

PubMed

Kashir, Junaid; Jones, Celine; Mounce, Ginny; Ramadan, Walaa M; Lemmon, Bernadette; Heindryckx, Bjorn; de Sutter, Petra; Parrington, John; Turner, Karen; Child, Tim; McVeigh, Enda; Coward, Kevin

2013-01-01

To examine whether similar levels of phospholipase C zeta (PLC-ζ) protein are present in sperm from men whose ejaculates resulted in normal oocyte activation, and to examine whether a predominant pattern of PLC-ζ localization is linked to normal oocyte activation ability. Laboratory study. University laboratory. Control subjects (men with proven oocyte activation capacity; n = 16) and men whose sperm resulted in recurrent intracytoplasmic sperm injection failure (oocyte activation deficient [OAD]; n = 5). Quantitative immunofluorescent analysis of PLC-ζ protein in human sperm. Total levels of PLC-ζ fluorescence, proportions of sperm exhibiting PLC-ζ immunoreactivity, and proportions of PLC-ζ localization patterns in sperm from control and OAD men. Sperm from control subjects presented a significantly higher proportion of sperm exhibiting PLC-ζ immunofluorescence compared with infertile men diagnosed with OAD (82.6% and 27.4%, respectively). Total levels of PLC-ζ in sperm from individual control and OAD patients exhibited significant variance, with sperm from 10 out of 16 (62.5%) exhibiting levels similar to OAD samples. Predominant PLC-ζ localization patterns varied between control and OAD samples with no predictable or consistent pattern. The results indicate that sperm from control men exhibited significant variance in total levels of PLC-ζ protein, as well as significant variance in the predominant localization pattern. Such variance may hinder the diagnostic application of quantitative PLC-ζ immunofluorescent analysis. Copyright © 2013 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

The Impact of Truth Surrogate Variance on Quality Assessment/Assurance in Wind Tunnel Testing

NASA Technical Reports Server (NTRS)

DeLoach, Richard

2016-01-01

Minimum data volume requirements for wind tunnel testing are reviewed and shown to depend on error tolerance, response model complexity, random error variance in the measurement environment, and maximum acceptable levels of inference error risk. Distinctions are made between such related concepts as quality assurance and quality assessment in response surface modeling, as well as between precision and accuracy. Earlier research on the scaling of wind tunnel tests is extended to account for variance in the truth surrogates used at confirmation sites in the design space to validate proposed response models. A model adequacy metric is presented that represents the fraction of the design space within which model predictions can be expected to satisfy prescribed quality specifications. The impact of inference error on the assessment of response model residuals is reviewed. The number of sites where reasonably well-fitted response models actually predict inadequately is shown to be considerably less than the number of sites where residuals are out of tolerance. The significance of such inference error effects on common response model assessment strategies is examined.

The role of multidimensional attentional abilities in academic skills of children with ADHD.

PubMed

Preston, Andrew S; Heaton, Shelley C; McCann, Sarah J; Watson, William D; Selke, Gregg

2009-01-01

Despite reports of academic difficulties in children with attention-deficit/hyperactivity disorder (ADHD), little is known about the relationship between performance on tests of academic achievement and measures of attention. The current study assessed intellectual ability, parent-reported inattention, academic achievement, and attention in 45 children (ages 7-15) diagnosed with ADHD. Hierarchical regressions were performed with selective, sustained, and attentional control/switching domains of the Test of Everyday Attention for Children as predictor variables and with performance on the Wechsler Individual Achievement Test-Second Edition as dependent variables. It was hypothesized that sustained attention and attentional control/switching would predict performance on achievement tests. Results demonstrate that attentional control/ switching accounted for a significant amount of variance in all academic areas (reading, math, and spelling), even after accounting for verbal IQ and parent-reported inattention. Sustained attention predicted variance only in math, whereas selective attention did not account for variance in any achievement domain. Therefore, attentional control/switching, which involves components of executive functions, plays an important role in academic performance.

Chronic Temporomandibular Disorders: disability, pain intensity and fear of movement.

PubMed

Gil-Martínez, Alfonso; Grande-Alonso, Mónica; López-de-Uralde-Villanueva, Ibai; López-López, Almudena; Fernández-Carnero, Josué; La Touche, Roy

2016-12-01

The objective was to compare and correlate disability, pain intensity, the impact of headache on daily life and the fear of movement between subgroups of patients with chronic temporomandibular disorder (TMD). A cross-sectional study was conducted in patients diagnosed with chronic painful TMD. Patients were divided into: 1) joint pain (JP); 2) muscle pain (MP); and 3) mixed pain. The following measures were included: Craniomandibular pain and disability (Craniofacial pain and disability inventory), neck disability (Neck Dsiability Index), pain intensity (Visual Analogue Scale), impact of headache (Headache Impact Test 6) and kinesiophobia (Tampa Scale of Kinesiophobia-11). A total of 154 patients were recruited. The mixed pain group showed significant differences compared with the JP group or MP group in neck disability (p < 0.001, d = 1.99; and p < 0.001, d = 1.17), craniomandibular pain and disability (p < 0.001, d = 1.34; and p < 0.001, d = 0.9, respectively), and impact of headache (p < 0.001, d = 1.91; and p < 0.001, d = 0.91, respectively). In addition, significant differences were observed between JP group and MP group for impact of headache (p < 0.001, d = 1.08). Neck disability was a significant covariate (37 % of variance) of craniomandibular pain and disability for the MP group (β = 0.62; p < 0.001). In the mixed chronic pain group, neck disability (β = 0.40; p < 0.001) and kinesiophobia (β = 0.30; p = 0.03) were significant covariate (33 % of variance) of craniomandibular pain and disability. Mixed chronic pain patients show greater craniomandibular and neck disability than patients diagnosed with chronic JP or MP. Neck disability predicted the variance of craniofacial pain and disability for patients with MP. Neck disability and kinesiophobia predicted the variance of craniofacial pain and disability for those with chronic mixed pain.

Biological maturity-associated variance in peak power output and momentum in academy rugby union players.

PubMed

Howard, Sean M A; Cumming, Sean P; Atkinson, Mark; Malina, Robert M

2016-11-01

The study aimed to evaluate the mediating effect of biological maturation on anthropometrical measurements, performance indicators and subsequent selection in a group of academy rugby union players. Fifty-one male players 14-17 years of age were assessed for height, weight and BMI, and percentage of predicted mature status attained at the time of observation was used as an indicator of maturity status. Following this, initial sprint velocity (ISV), Wattbike peak power output (PPO) and initial sprint momentum (ISM) were assessed. A bias towards on-time (n = 44) and early (n = 7) maturers was evident in the total sample and magnified with age cohort. Relative to UK reference values, weight and height were above the 90th and 75th centiles, respectively. Significant (p ≤ .01) correlations were observed between maturity status and BMI (r = .48), weight (r = .63) and height (r = .48). Regression analysis (controlling for age) revealed that maturity status and height explained 68% of ISM variance; however, including BMI in the model attenuated the influence of maturity status below statistical significance (p = .72). Height and BMI explained 51% of PPO variance, while no initial significant predictors were identified for ISV. The sample consisted of players who were on-time and early in maturation with no late maturers represented. This was attributable, in part, to the mediating effect of maturation on body size, which, in turn, predicted performance variables.

Impact of source collinearity in simulated PM 2.5 data on the PMF receptor model solution

NASA Astrophysics Data System (ADS)

Habre, Rima; Coull, Brent; Koutrakis, Petros

2011-12-01

Positive Matrix Factorization (PMF) is a factor analytic model used to identify particle sources and to estimate their contributions to PM 2.5 concentrations observed at receptor sites. Collinearity in source contributions due to meteorological conditions introduces uncertainty in the PMF solution. We simulated datasets of speciated PM 2.5 concentrations associated with three ambient particle sources: "Motor Vehicle" (MV), "Sodium Chloride" (NaCl), and "Sulfur" (S), and we varied the correlation structure between their mass contributions to simulate collinearity. We analyzed the datasets in PMF using the ME-2 multilinear engine. The Pearson correlation coefficients between the simulated and PMF-predicted source contributions and profiles are denoted by " G correlation" and " F correlation", respectively. In sensitivity analyses, we examined how the means or variances of the source contributions affected the stability of the PMF solution with collinearity. The % errors in predicting the average source contributions were 23, 80 and 23% for MV, NaCl, and S, respectively. On average, the NaCl contribution was overestimated, while MV and S contributions were underestimated. The ability of PMF to predict the contributions and profiles of the three sources deteriorated significantly as collinearity in their contributions increased. When the mean of NaCl or variance of NaCl and MV source contributions was increased, the deterioration in G correlation with increasing collinearity became less significant, and the ability of PMF to predict the NaCl and MV loading profiles improved. When the three factor profiles were simulated to share more elements, the decrease in G and F correlations became non-significant. Our findings agree with previous simulation studies reporting that correlated sources are predicted with higher error and bias. Consequently, the power to detect significant concentration-response estimates in health effect analyses weakens.

Prediction models of health-related quality of life in different neck pain conditions: a cross-sectional study.

PubMed

Beltran-Alacreu, Hector; López-de-Uralde-Villanueva, Ibai; Calvo-Lobo, César; La Touche, Roy; Cano-de-la-Cuerda, Roberto; Gil-Martínez, Alfonso; Fernández-Ayuso, David; Fernández-Carnero, Josué

2018-01-01

The main aim of the study was to predict the health-related quality of life (HRQoL) based on physical, functional, and psychological measures in patients with different types of neck pain (NP). This cross-sectional study included 202 patients from a primary health center and the physiotherapy outpatient department of a hospital. Patients were divided into four groups according to their NP characteristics: chronic (CNP), acute whiplash (WHIP), chronic NP associated with temporomandibular dysfunction (NP-TMD), or chronic NP associated with chronic primary headache (NP-PH). The following measures were performed: Short Form-12 Health Survey (SF-12), Neck Disability Index (NDI), visual analog scale (VAS), State-Trait Anxiety Inventory (STAI), Beck Depression Inventory (BECK), and cervical range of movement (CROM). The regression models based on the SF-12 total HRQoL for CNP and NP-TMD groups showed that only NDI was a significant predictor of the worst HRQoL (48.9% and 48.4% of the variance, respectively). In the WHIP group, the regression model showed that BECK was the only significant predictor variable for the worst HRQoL (31.7% of the variance). Finally, in the NP-PH group, the regression showed that the BECK, STAI, and VAS model predicted the worst HRQoL (75.1% of the variance). Chronic nonspecific NP and chronic NP associated with temporomandibular dysfunction were the main predictors of neck disability. In addition, depression, anxiety, and pain were the main predictors of WHIP or primary headache associated with CNP.

Effects of social contact and zygosity on 21-y weight change in male twins.

PubMed

McCaffery, Jeanne M; Franz, Carol E; Jacobson, Kristen; Leahey, Tricia M; Xian, Hong; Wing, Rena R; Lyons, Michael J; Kremen, William S

2011-08-01

Recent evidence indicates that social contact is related to similarities in weight gain over time. However, no studies have examined this effect in a twin design, in which genetic and other environmental effects can also be estimated. We determined whether the frequency of social contact is associated with similarity in weight change from young adulthood (mean age: 20 y) to middle age (mean age: 41 y) in twins and quantified the percentage of variance in weight change attributable to social contact, genetic factors, and other environmental influences. Participants were 1966 monozygotic and 1529 dizygotic male twin pairs from the Vietnam-Era Twin Registry. Regression models tested whether frequency of social contact and zygosity predicted twin pair similarity in body mass index (BMI) change and weight change. Twin modeling was used to partition the percentage variance attributable to social contact, genetic, and other environmental effects. Twins gained an average of 3.99 BMI units, or 13.23 kg (29.11 lb), over 21 y. In regression models, both zygosity (P < 0.001) and degree of social contact (P < 0.02) significantly predicted twin pair similarity in BMI change. In twin modeling, social contact between twins contributed 16% of the variance in BMI change (P < 0.001), whereas genetic factors contributed 42%, with no effect of additional shared environmental factors (1%). Similar results were obtained for weight change. Frequency of social contact significantly predicted twin pair similarity in BMI and weight change over 21 y, independent of zygosity and other shared environmental influences.

Examining predictors of healthcare utilization in youth with inflammatory bowel disease.

PubMed

Wojtowicz, Andrea A; Plevinsky, Jill M; Poulopoulos, Natasha; Schurman, Jennifer V; Greenley, Rachel N

2016-04-01

Traditional definitions of healthcare utilization (HCU) emphasize clinical visits and procedures. Clinic calls, an understudied form of HCU, occur with high frequency. Understanding and examining predictors of HCU, such as disease activity and parent distress, may help reduce overutilization. A total of 68 adolescents with inflammatory bowel disease [IBD; mean (SD) =14.18 (1.92) years] and their parents participated. Parent distress was assessed through parent report on the PedsQL Family Impact Module, and physicians provided ratings of patient disease activity using the Physician's Global Assessment index. Medical record reviews yielded HCU and clinic call information for 12 months after enrollment. HCU was operationalized as the total number of routine and sick gastrointestinal clinic visits, Emergency room visits, and IBD-related hospitalizations. A call composite reflected the total number of calls related to IBD symptoms/illness. Disease activity and parent distress predicted 12% of the variance in calls and 12% of the variance in HCU. Disease activity was the only significant predictor of clinic calls after accounting for the impact of other predictors; however, parent distress was the only individual variable that contributed significant variance to the prediction of HCU after accounting for other predictors. Greater parent distress and disease activity together predicted HCU and clinic calls. Disease activity was the most salient predictor of calls, whereas parent distress was the most salient predictor of in-person HCU. Clinic calls should not be overlooked as a form of HCU, as communication that takes place outside of scheduled appointments utilizes resources and may indicate poorer disease control.

Does trait affectivity predict work-to-family conflict and enrichment beyond job characteristics?

PubMed

Tement, Sara; Korunka, Christian

2013-01-01

The present study examines whether negative and positive affectivity (NA and PA, respectively) predict different forms of work-to-family conflict (WFC-time, WFC-strain, WFC-behavior) and enrichment (WFE-development, WFE-affect, WFE-capital) beyond job characteristics (workload, autonomy, variety, workplace support). Furthermore, interactions between job characteristics and trait affectivity while predicting WFC and WFE were examined. Using a large sample of Slovenian employees (N = 738), NA and PA were found to explain variance in WFC as well as in WFE above and beyond job characteristics. More precisely, NA significantly predicted WFC, whereas PA significantly predicted WFE. In addition, several interactive effects were found to predict forms of WFC and WFE. These results highlight the importance of trait affectivity in work-family research. They provide further support for the crucial impact of job characteristics as well.

Speeding Up Microevolution: The Effects of Increasing Temperature on Selection and Genetic Variance in a Wild Bird Population

PubMed Central

Husby, Arild; Visser, Marcel E.; Kruuk, Loeske E. B.

2011-01-01

The amount of genetic variance underlying a phenotypic trait and the strength of selection acting on that trait are two key parameters that determine any evolutionary response to selection. Despite substantial evidence that, in natural populations, both parameters may vary across environmental conditions, very little is known about the extent to which they may covary in response to environmental heterogeneity. Here we show that, in a wild population of great tits (Parus major), the strength of the directional selection gradients on timing of breeding increased with increasing spring temperatures, and that genotype-by-environment interactions also predicted an increase in additive genetic variance, and heritability, of timing of breeding with increasing spring temperature. Consequently, we therefore tested for an association between the annual selection gradients and levels of additive genetic variance expressed each year; this association was positive, but non-significant. However, there was a significant positive association between the annual selection differentials and the corresponding heritability. Such associations could potentially speed up the rate of micro-evolution and offer a largely ignored mechanism by which natural populations may adapt to environmental changes. PMID:21408101

Routine blood tests to predict liver fibrosis in chronic hepatitis C.

PubMed

Hsieh, Yung-Yu; Tung, Shui-Yi; Lee, Kamfai; Wu, Cheng-Shyong; Wei, Kuo-Liang; Shen, Chien-Heng; Chang, Te-Sheng; Lin, Yi-Hsiung

2012-02-28

To verify the usefulness of FibroQ for predicting fibrosis in patients with chronic hepatitis C, compared with other noninvasive tests. This retrospective cohort study included 237 consecutive patients with chronic hepatitis C who had undergone percutaneous liver biopsy before treatment. FibroQ, aspartate aminotransferase (AST)/alanine aminotransferase ratio (AAR), AST to platelet ratio index, cirrhosis discriminant score, age-platelet index (API), Pohl score, FIB-4 index, and Lok's model were calculated and compared. FibroQ, FIB-4, AAR, API and Lok's model results increased significantly as fibrosis advanced (analysis of variance test: P < 0.001). FibroQ trended to be superior in predicting significant fibrosis score in chronic hepatitis C compared with other noninvasive tests. FibroQ is a simple and useful test for predicting significant fibrosis in patients with chronic hepatitis C.

The predictive value of self-report questions in a clinical decision rule for pediatric lead poisoning screening.

PubMed

Kaplowitz, Stan A; Perlstadt, Harry; D'Onofrio, Gail; Melnick, Edward R; Baum, Carl R; Kirrane, Barbara M; Post, Lori A

2012-01-01

We derived a clinical decision rule for determining which young children need testing for lead poisoning. We developed an equation that combines lead exposure self-report questions with the child's census-block housing and socioeconomic characteristics, personal demographic characteristics, and Medicaid status. This equation better predicts elevated blood lead level (EBLL) than one using ZIP code and Medicaid status. A survey regarding potential lead exposure was administered from October 2001 to January 2003 to Michigan parents at pediatric clinics (n=3,396). These self-report survey data were linked to a statewide clinical registry of blood lead level (BLL) tests. Sensitivity and specificity were calculated and then used to estimate the cost-effectiveness of the equation. The census-block group prediction equation explained 18.1% of the variance in BLLs. Replacing block group characteristics with the self-report questions and dichotomized ZIP code risk explained only 12.6% of the variance. Adding three self-report questions to the census-block group model increased the variance explained to 19.9% and increased specificity with no loss in sensitivity in detecting EBLLs of ≥ 10 micrograms per deciliter. Relying solely on self-reports of lead exposure predicted BLL less effectively than the block group model. However, adding three of 13 self-report questions to our clinical decision rule significantly improved prediction of which children require a BLL test. Using the equation as the clinical decision rule would annually eliminate more than 7,200 unnecessary tests in Michigan and save more than $220,000.

Thermospheric mass density model error variance as a function of time scale

NASA Astrophysics Data System (ADS)

Emmert, J. T.; Sutton, E. K.

2017-12-01

In the increasingly crowded low-Earth orbit environment, accurate estimation of orbit prediction uncertainties is essential for collision avoidance. Poor characterization of such uncertainty can result in unnecessary and costly avoidance maneuvers (false positives) or disregard of a collision risk (false negatives). Atmospheric drag is a major source of orbit prediction uncertainty, and is particularly challenging to account for because it exerts a cumulative influence on orbital trajectories and is therefore not amenable to representation by a single uncertainty parameter. To address this challenge, we examine the variance of measured accelerometer-derived and orbit-derived mass densities with respect to predictions by thermospheric empirical models, using the data-minus-model variance as a proxy for model uncertainty. Our analysis focuses mainly on the power spectrum of the residuals, and we construct an empirical model of the variance as a function of time scale (from 1 hour to 10 years), altitude, and solar activity. We find that the power spectral density approximately follows a power-law process but with an enhancement near the 27-day solar rotation period. The residual variance increases monotonically with altitude between 250 and 550 km. There are two components to the variance dependence on solar activity: one component is 180 degrees out of phase (largest variance at solar minimum), and the other component lags 2 years behind solar maximum (largest variance in the descending phase of the solar cycle).

Perturbed threat monitoring following a traumatic event predicts risk for post-traumatic stress disorder.

PubMed

Naim, R; Wald, I; Lior, A; Pine, D S; Fox, N A; Sheppes, G; Halpern, P; Bar-Haim, Y

2014-07-01

Post-traumatic stress disorder (PTSD) is a chronic and difficult to treat psychiatric disorder. Objective, performance-based diagnostic markers that uniquely index risk for PTSD above and beyond subjective self-report markers could inform attempts to improve prevention and early intervention. We evaluated the predictive value of threat-related attention bias measured immediately after a potentially traumatic event, as a risk marker for PTSD at a 3-month follow-up. We measured the predictive contribution of attentional threat bias above and beyond that of the more established marker of risk for PTSD, self-reported psychological dissociation. Dissociation symptoms and threat-related attention bias were measured in 577 motor vehicle accident (MVA) survivors (mean age = 35.02 years, 356 males) within 24 h of admission to an emergency department (ED) of a large urban hospital. PTSD symptoms were assessed at a 3-month follow-up using the Clinician-Administered PTSD Scale (CAPS). Self-reported dissociation symptoms significantly accounted for 16% of the variance in PTSD at follow-up, and attention bias toward threat significantly accounted for an additional 4% of the variance in PTSD. Threat-related attention bias can be reliably measured in the context of a hospital ED and significantly predicts risk for later PTSD. Possible mechanisms underlying the association between threat bias following a potentially traumatic event and risk for PTSD are discussed. The potential application of an attention bias modification treatment (ABMT) tailored to reduce risk for PTSD is suggested.

Optimal design criteria - prediction vs. parameter estimation

NASA Astrophysics Data System (ADS)

Waldl, Helmut

2014-05-01

G-optimality is a popular design criterion for optimal prediction, it tries to minimize the kriging variance over the whole design region. A G-optimal design minimizes the maximum variance of all predicted values. If we use kriging methods for prediction it is self-evident to use the kriging variance as a measure of uncertainty for the estimates. Though the computation of the kriging variance and even more the computation of the empirical kriging variance is computationally very costly and finding the maximum kriging variance in high-dimensional regions can be time demanding such that we cannot really find the G-optimal design with nowadays available computer equipment in practice. We cannot always avoid this problem by using space-filling designs because small designs that minimize the empirical kriging variance are often non-space-filling. D-optimality is the design criterion related to parameter estimation. A D-optimal design maximizes the determinant of the information matrix of the estimates. D-optimality in terms of trend parameter estimation and D-optimality in terms of covariance parameter estimation yield basically different designs. The Pareto frontier of these two competing determinant criteria corresponds with designs that perform well under both criteria. Under certain conditions searching the G-optimal design on the above Pareto frontier yields almost as good results as searching the G-optimal design in the whole design region. In doing so the maximum of the empirical kriging variance has to be computed only a few times though. The method is demonstrated by means of a computer simulation experiment based on data provided by the Belgian institute Management Unit of the North Sea Mathematical Models (MUMM) that describe the evolution of inorganic and organic carbon and nutrients, phytoplankton, bacteria and zooplankton in the Southern Bight of the North Sea.

Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: prediction accuracy implications

PubMed Central

Bouvet, J-M; Makouanzi, G; Cros, D; Vigneron, Ph

2016-01-01

Hybrids are broadly used in plant breeding and accurate estimation of variance components is crucial for optimizing genetic gain. Genome-wide information may be used to explore models designed to assess the extent of additive and non-additive variance and test their prediction accuracy for the genomic selection. Ten linear mixed models, involving pedigree- and marker-based relationship matrices among parents, were developed to estimate additive (A), dominance (D) and epistatic (AA, AD and DD) effects. Five complementary models, involving the gametic phase to estimate marker-based relationships among hybrid progenies, were developed to assess the same effects. The models were compared using tree height and 3303 single-nucleotide polymorphism markers from 1130 cloned individuals obtained via controlled crosses of 13 Eucalyptus urophylla females with 9 Eucalyptus grandis males. Akaike information criterion (AIC), variance ratios, asymptotic correlation matrices of estimates, goodness-of-fit, prediction accuracy and mean square error (MSE) were used for the comparisons. The variance components and variance ratios differed according to the model. Models with a parent marker-based relationship matrix performed better than those that were pedigree-based, that is, an absence of singularities, lower AIC, higher goodness-of-fit and accuracy and smaller MSE. However, AD and DD variances were estimated with high s.es. Using the same criteria, progeny gametic phase-based models performed better in fitting the observations and predicting genetic values. However, DD variance could not be separated from the dominance variance and null estimates were obtained for AA and AD effects. This study highlighted the advantages of progeny models using genome-wide information. PMID:26328760

Getting Answers to Natural Language Questions on the Web.

ERIC Educational Resources Information Center

Radev, Dragomir R.; Libner, Kelsey; Fan, Weiguo

2002-01-01

Describes a study that investigated the use of natural language questions on Web search engines. Highlights include query languages; differences in search engine syntax; and results of logistic regression and analysis of variance that showed aspects of questions that predicted significantly different performances, including the number of words,…

Job Preferences in the Anticipatory Socialization Phase: A Comparison of Two Matching Models.

ERIC Educational Resources Information Center

Moss, Mira K.; Frieze, Irene Hanson

1993-01-01

Responses from 86 business administration graduate students tested (1) a model matching self-concept to development of job preferences and (2) an expectancy-value model. Both models significantly predicted job preferences; a higher proportion of variance was explained by the expectancy-value model. (SK)

A mobile-mobile transport model for simulating reactive transport in connected heterogeneous fields

NASA Astrophysics Data System (ADS)

Lu, Chunhui; Wang, Zhiyuan; Zhao, Yue; Rathore, Saubhagya Singh; Huo, Jinge; Tang, Yuening; Liu, Ming; Gong, Rulan; Cirpka, Olaf A.; Luo, Jian

2018-05-01

Mobile-immobile transport models can be effective in reproducing heavily tailed breakthrough curves of concentration. However, such models may not adequately describe transport along multiple flow paths with intermediate velocity contrasts in connected fields. We propose using the mobile-mobile model for simulating subsurface flow and associated mixing-controlled reactive transport in connected fields. This model includes two local concentrations, one in the fast- and the other in the slow-flow domain, which predict both the concentration mean and variance. The normalized total concentration variance within the flux is found to be a non-monotonic function of the discharge ratio with a maximum concentration variance at intermediate values of the discharge ratio. We test the mobile-mobile model for mixing-controlled reactive transport with an instantaneous, irreversible bimolecular reaction in structured and connected random heterogeneous domains, and compare the performance of the mobile-mobile to the mobile-immobile model. The results indicate that the mobile-mobile model generally predicts the concentration breakthrough curves (BTCs) of the reactive compound better. Particularly, for cases of an elliptical inclusion with intermediate hydraulic-conductivity contrasts, where the travel-time distribution shows bimodal behavior, the prediction of both the BTCs and maximum product concentration is significantly improved. Our results exemplify that the conceptual model of two mobile domains with diffusive mass transfer in between is in general good for predicting mixing-controlled reactive transport, and particularly so in cases where the transfer in the low-conductivity zones is by slow advection rather than diffusion.

Evaluation of non-additive genetic variation in feed-related traits of broiler chickens.

PubMed

Li, Y; Hawken, R; Sapp, R; George, A; Lehnert, S A; Henshall, J M; Reverter, A

2017-03-01

Genome-wide association mapping and genomic predictions of phenotype of individuals in livestock are predominately based on the detection and estimation of additive genetic effects. Non-additive genetic effects are largely ignored. Studies in animals, plants, and humans to assess the impact of non-additive genetic effects in genetic analyses have led to differing conclusions. In this paper, we examined the consequences of including non-additive genetic effects in genome-wide association mapping and genomic prediction of total genetic values in a commercial population of 5,658 broiler chickens genotyped for 45,176 single nucleotide polymorphism (SNP) markers. We employed mixed-model equations and restricted maximum likelihood to analyze 7 feed related traits (TRT1 - TRT7). Dominance variance accounted for a significant proportion of the total genetic variance in all 7 traits, ranging from 29.5% for TRT1 to 58.4% for TRT7. Using a 5-fold cross-validation schema, we found that in spite of the large dominance component, including the estimated dominance effects in the prediction of total genetic values did not improve the accuracy of the predictions for any of the phenotypes. We offer some possible explanations for this counter-intuitive result including the possible confounding of dominance deviations with common environmental effects such as hatch, different directional effects of SNP additive and dominance variations, and the gene-gene interactions' failure to contribute to the level of variance. © 2016 Poultry Science Association Inc.

A log-sinh transformation for data normalization and variance stabilization

NASA Astrophysics Data System (ADS)

Wang, Q. J.; Shrestha, D. L.; Robertson, D. E.; Pokhrel, P.

2012-05-01

When quantifying model prediction uncertainty, it is statistically convenient to represent model errors that are normally distributed with a constant variance. The Box-Cox transformation is the most widely used technique to normalize data and stabilize variance, but it is not without limitations. In this paper, a log-sinh transformation is derived based on a pattern of errors commonly seen in hydrological model predictions. It is suited to applications where prediction variables are positively skewed and the spread of errors is seen to first increase rapidly, then slowly, and eventually approach a constant as the prediction variable becomes greater. The log-sinh transformation is applied in two case studies, and the results are compared with one- and two-parameter Box-Cox transformations.

A long-term predictive validity study: can the CDI Short Form be used to predict language and early literacy skills four years later?

PubMed

Can, Dilara Deniz; Ginsburg-Block, Marika; Golinkoff, Roberta Michnick; Hirsh-Pasek, Kathryn

2013-09-01

This longitudinal study examined the predictive validity of the MacArthur Communicative Developmental Inventories-Short Form (CDI-SF), a parent report questionnaire about children's language development (Fenson, Pethick, Renda, Cox, Dale & Reznick, 2000). Data were first gathered from parents on the CDI-SF vocabulary scores for seventy-six children (mean age=1 ; 10). Four years later (mean age=6 ; 1), children were assessed on language outcomes (expressive vocabulary, syntax, semantics and pragmatics) and code-related skills, including phonemic awareness, word recognition and decoding skills. Hierarchical regression analyses revealed that early expressive vocabulary accounted for 17% of the variance in picture vocabulary, 11% of the variance in syntax, and 7% of the variance in semantics, while not accounting for any variance in pragmatics in kindergarten. CDI-SF scores did not predict code-related skills in kindergarten. The importance of early vocabulary skills for later language development and CDI-SF as a valuable research tool are discussed.

[Impacts of biological and family factors on lexical and intellectual development in Mandarin-speaking children].

PubMed

Niu, Jie; Chen, Yong-Xiang; Zhu, Li-Qi

2015-07-01

To investigate the impacts of biological factors (age and sex) and family factors (socioeconomic status and parenting style) on the early lexical and intellectual development of children in a longitudinal tracking study. A total of 38 Mandarin-speaking children aged from 18 to 24 months were surveyed using the Putonghua Chinese Communicative Development Inventory (PCDI), the Ages and Stages Questionnaire (ASQ), and a self-designed Questionnaire for Parents. All of the subjects were retested using PCDI and ASQ after 6 months. Biological factors accounted for 65% of the variance in lexical development, 10% of which was attributed to gender, in the first survey. After six months, the contribution of age decreased to 26% and gender had no significant impact. Lexical development could positively predict the intellectual development of children. When age and gender were controlled, it accounted for 22% of the variance in intellectual development. Family socioeconomic factors had no significant impacts on lexical and intellectual development. Children's recognition of people and objects around them with guidance of parents in parenting styles could positively predict the intellectual development of children six months later, which accounted for 10% of the variance. Biological factors play an important role in the early lexical development of children. However, the influence decreases with the increase of age (months). Biological factors, lexical development, and parenting style have a combined influence on children's intellectual development.

Analysis of conditional genetic effects and variance components in developmental genetics.

PubMed

Zhu, J

1995-12-01

A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.

Analysis of Conditional Genetic Effects and Variance Components in Developmental Genetics

PubMed Central

Zhu, J.

1995-01-01

A genetic model with additive-dominance effects and genotype X environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t - 1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects. PMID:8601500

Modeling heterogeneous (co)variances from adjacent-SNP groups improves genomic prediction for milk protein composition traits.

PubMed

Gebreyesus, Grum; Lund, Mogens S; Buitenhuis, Bart; Bovenhuis, Henk; Poulsen, Nina A; Janss, Luc G

2017-12-05

Accurate genomic prediction requires a large reference population, which is problematic for traits that are expensive to measure. Traits related to milk protein composition are not routinely recorded due to costly procedures and are considered to be controlled by a few quantitative trait loci of large effect. The amount of variation explained may vary between regions leading to heterogeneous (co)variance patterns across the genome. Genomic prediction models that can efficiently take such heterogeneity of (co)variances into account can result in improved prediction reliability. In this study, we developed and implemented novel univariate and bivariate Bayesian prediction models, based on estimates of heterogeneous (co)variances for genome segments (BayesAS). Available data consisted of milk protein composition traits measured on cows and de-regressed proofs of total protein yield derived for bulls. Single-nucleotide polymorphisms (SNPs), from 50K SNP arrays, were grouped into non-overlapping genome segments. A segment was defined as one SNP, or a group of 50, 100, or 200 adjacent SNPs, or one chromosome, or the whole genome. Traditional univariate and bivariate genomic best linear unbiased prediction (GBLUP) models were also run for comparison. Reliabilities were calculated through a resampling strategy and using deterministic formula. BayesAS models improved prediction reliability for most of the traits compared to GBLUP models and this gain depended on segment size and genetic architecture of the traits. The gain in prediction reliability was especially marked for the protein composition traits β-CN, κ-CN and β-LG, for which prediction reliabilities were improved by 49 percentage points on average using the MT-BayesAS model with a 100-SNP segment size compared to the bivariate GBLUP. Prediction reliabilities were highest with the BayesAS model that uses a 100-SNP segment size. The bivariate versions of our BayesAS models resulted in extra gains of up to 6% in prediction reliability compared to the univariate versions. Substantial improvement in prediction reliability was possible for most of the traits related to milk protein composition using our novel BayesAS models. Grouping adjacent SNPs into segments provided enhanced information to estimate parameters and allowing the segments to have different (co)variances helped disentangle heterogeneous (co)variances across the genome.

Psychosocial work characteristics predicting daytime sleepiness in day and shift workers.

PubMed

Takahashi, Masaya; Nakata, Akinori; Haratani, Takashi; Otsuka, Yasumasa; Kaida, Kosuke; Fukasawa, Kenji

2006-01-01

Characteristics of work organization other than working time arrangements may contribute importantly to daytime sleepiness. The present study was designed to identify the psychosocial factors at work that predict daytime sleepiness in a sample of day and shift workers. Participants working at a pulp and chemical factory completed an annual questionnaire regarding psychosocial factors at work using the U.S. National Institute for Occupational Safety and Health Generic Job Stress Questionnaire (i.e., quantitative workload, variance in workload, job control, support from supervisor, coworkers, or family/friends, job satisfaction, and depressive symptoms), as well as daytime sleepiness (through the Epworth Sleepiness Scale [ESS]) and sleep disturbances for three years starting in 2002 (response rates, 94.6-99.0%). The present analysis included 55 day workers (11 women) and 57 shift workers (all men) who participated in all three years of the study, worked under the same work schedule throughout the study period, and had no missing data on any of the daytime sleep items. A repeated-measures analysis of covariance (ANCOVA) was used to test the effects of work schedule (day vs. shift work) and psychosocial factors at work in 2002 on the ESS scores in subsequent years, with sleep duration, insomnia symptoms, chronic diseases, and sleepiness levels at baseline as covariates. Given significant and near-significant interactions of work schedules with psychosocial factor or study year, the ANCOVA, with the factors of psychosocial work characteristics and study year, was performed by type of work schedule. The results indicated a significant main effect of psychosocial work characteristics (p = 0.010, partial eng2 = 0.14) and an almost significant main effect of study year (p = 0.067, partial eng2 = 0.06) and interaction between psychosocial work characteristics and study year (p = 0.085, partial eng2 = 0.06) for variance in workload among the day work group. The day workers reporting high variance in workload in 2002 exhibited significantly higher ESS scores in 2003 and 2004 than did those reporting low variance in workload. The ANCOVA for the shift work group showed a main effect of psychosocial work characteristics for job satisfaction (p = 0.026, partial eng2 = 0.10) and depressive symptoms (p = 0.094, partial eng2 = 0.06) with the interaction between psychosocial work characteristics and study year for job satisfaction (p = 0.172, partial eng2 = 0.04) and depressive symptoms (p = 0.035, partial eng2 = 0.07). The shift workers with low job satisfaction and high symptoms of depression in 2002 showed significantly greater ESS scores in 2003 and/or 2004 than did those with opposite characteristics. These results may suggest a potential predictive value of variance in workload for day workers as well as job satisfaction and depressive symptoms for shift workers with respect to daytime sleepiness. The present findings may imply that redesigning these aspects of work environment would be of help in managing daytime sleepiness.

Waist Circumference Adjusted for Body Mass Index and Intra-Abdominal Fat Mass

PubMed Central

Berentzen, Tina Landsvig; Ängquist, Lars; Kotronen, Anna; Borra, Ronald; Yki-Järvinen, Hannele; Iozzo, Patricia; Parkkola, Riitta; Nuutila, Pirjo; Ross, Robert; Allison, David B.; Heymsfield, Steven B.; Overvad, Kim; Sørensen, Thorkild I. A.; Jakobsen, Marianne Uhre

2012-01-01

Background The association between waist circumference (WC) and mortality is particularly strong and direct when adjusted for body mass index (BMI). One conceivable explanation for this association is that WC adjusted for BMI is a better predictor of the presumably most harmful intra-abdominal fat mass (IAFM) than WC alone. We studied the prediction of abdominal subcutaneous fat mass (ASFM) and IAFM by WC alone and by addition of BMI as an explanatory factor. Methodology/Principal Findings WC, BMI and magnetic resonance imaging data from 742 men and women who participated in clinical studies in Canada and Finland were pooled. Total adjusted squared multiple correlation coefficients (R2) of ASFM and IAFM were calculated from multiple linear regression models with WC and BMI as explanatory variables. Mean BMI and WC of the participants in the pooled sample were 30 kg/m2 and 102 cm, respectively. WC explained 29% of the variance in ASFM and 51% of the variance in IAFM. Addition of BMI to WC added 28% to the variance explained in ASFM, but only 1% to the variance explained in IAFM. Results in subgroups stratified by study center, sex, age, obesity level and type 2 diabetes status were not systematically different. Conclusion/Significance The prediction of IAFM by WC is not improved by addition of BMI. PMID:22384179

Predicting fifth-grade students' understanding of ecological science concepts with motivational and cognitive variables

NASA Astrophysics Data System (ADS)

Alao, Solomon

The need to identify factors that contribute to students' understanding of ecological concepts has been widely expressed in recent literature. The purpose of this study was to investigate the relationship between fifth grade students' prior knowledge, learning strategies, interest, and learning goals and their conceptual understanding of ecological science concepts. Subject were 72 students from three fifth grade classrooms located in a metropolitan area of the eastern United States. Students completed the goal commitment, interest, and strategy use questionnaire (GISQ), and a knowledge test designed to assess their prior knowledge and conceptual understanding of ecological science concepts. The learning goals scale assessed intentions to try to learn and understand ecological concepts. The interest scale assessed the feeling and value-related valences that students ascribed to science and ecological science concepts. The strategy use scale assessed the use of two cognitive strategies (monitoring and elaboration). The knowledge test assessed students' understanding of ecological concepts (the relationship between living organisms and their environment). Scores on all measures were examined for gender differences; no significant gender differences were observed. The motivational and cognitive variables contributed to students' understanding of ecological concepts. After accounting for interest, learning goals, and strategy use, prior knowledge accounted for 28% of the total variance in conceptual understanding. After accounting for prior knowledge, interest, learning goals, and strategy use explained 7%, 6%, and 4% of the total variance in conceptual understanding, respectively. More importantly, these variables were interrelated to each other and to conceptual understanding. After controlling for prior knowledge, learning goals, and strategy use, interest did not predict the variance in conceptual understanding. After controlling for prior knowledge, interest, and strategy use, learning goals did not predict the variance in conceptual understanding. And, after controlling for prior knowledge, interest, and learning goals, strategy use did not predict the variance in conceptual understanding. Results of this study indicated that prior knowledge, interest, learning goals, and strategy use should be included in theoretical models design to explain and to predict fifth grade students' understanding of ecological concepts. Results of this study further suggested that curriculum developers and science teachers need to take fifth grade students' prior knowledge of ecological concepts, interest in science and ecological concepts; intentions to learn and understand ecological concepts, and use of cognitive strategies into account when designing instructional contexts to support these students' understanding of ecological concepts.

Prediction of psychological functioning one year after the predictive test for Huntington's disease and impact of the test result on reproductive decision making.

PubMed Central

Decruyenaere, M; Evers-Kiebooms, G; Boogaerts, A; Cassiman, J J; Cloostermans, T; Demyttenaere, K; Dom, R; Fryns, J P; Van den Berghe, H

1996-01-01

For people at risk for Huntington's disease, the anxiety and uncertainty about the future may be very burdensome and may be an obstacle to personal decision making about important life issues, for example, procreation. For some at risk persons, this situation is the reason for requesting predictive DNA testing. The aim of this paper is two-fold. First, we want to evaluate whether knowing one's carrier status reduces anxiety and uncertainty and whether it facilitates decision making about procreation. Second, we endeavour to identify pretest predictors of psychological adaptation one year after the predictive test (psychometric evaluation of general anxiety, depression level, and ego strength). The impact of the predictive test result was assessed in 53 subjects tested, using pre- and post-test psychometric measurement and self-report data of follow up interviews. Mean anxiety and depression levels were significantly decreased one year after a good test result; there was no significant change in the case of a bad test result. The mean personality profile, including ego strength, remained unchanged one year after the test. The study further shows that the test result had a definite impact on reproductive decision making. Stepwise multiple regression analyses were used to select the best predictors of the subject's post-test reactions. The results indicate that a careful evaluation of pretest ego strength, depression level, and coping strategies may be helpful in predicting post-test reactions, independently of the carrier status. Test result (carrier/ non-carrier), gender, and age did not significantly contribute to the prediction. About one third of the variance of post-test anxiety and depression level and more than half of the variance of ego strength was explained, implying that other psychological or social aspects should also be taken into account when predicting individual post-test reactions. PMID:8880572

Lexical analysis in schizophrenia: how emotion and social word use informs our understanding of clinical presentation.

PubMed

Minor, Kyle S; Bonfils, Kelsey A; Luther, Lauren; Firmin, Ruth L; Kukla, Marina; MacLain, Victoria R; Buck, Benjamin; Lysaker, Paul H; Salyers, Michelle P

2015-05-01

The words people use convey important information about internal states, feelings, and views of the world around them. Lexical analysis is a fast, reliable method of assessing word use that has shown promise for linking speech content, particularly in emotion and social categories, with psychopathological symptoms. However, few studies have utilized lexical analysis instruments to assess speech in schizophrenia. In this exploratory study, we investigated whether positive emotion, negative emotion, and social word use was associated with schizophrenia symptoms, metacognition, and general functioning in a schizophrenia cohort. Forty-six participants generated speech during a semi-structured interview, and word use categories were assessed using a validated lexical analysis measure. Trained research staff completed symptom, metacognition, and functioning ratings using semi-structured interviews. Word use categories significantly predicted all variables of interest, accounting for 28% of the variance in symptoms and 16% of the variance in metacognition and general functioning. Anger words, a subcategory of negative emotion, significantly predicted greater symptoms and lower functioning. Social words significantly predicted greater metacognition. These findings indicate that lexical analysis instruments have the potential to play a vital role in psychosocial assessments of schizophrenia. Future research should replicate these findings and examine the relationship between word use and additional clinical variables across the schizophrenia-spectrum. Copyright © 2015 Elsevier Ltd. All rights reserved.

Can parenting practices predict externalizing behavior problems among children with hearing impairment?

PubMed

Pino, María J; Castillo, Rosa A; Raya, Antonio; Herruzo, Javier

2017-11-09

To identify possible differences in the level of externalizing behavior problems among children with and without hearing impairment and determine whether any relationship exists between this type of problem and parenting practices. The Behavior Assessment System for Children was used to evaluate externalizing variables in a sample of 118 boys and girls divided into two matched groups: 59 with hearing disorders and 59 normal-hearing controls. Significant between-group differences were found in hyperactivity, behavioral problems, and externalizing problems, but not in aggression. Significant differences were also found in various aspects of parenting styles. A model for predicting externalizing behavior problems was constructed, achieving a predicted explained variance of 50%. Significant differences do exist between adaptation levels in children with and without hearing impairment. Parenting style also plays an important role.

Global Sensitivity Analysis and Parameter Calibration for an Ecosystem Carbon Model

NASA Astrophysics Data System (ADS)

Safta, C.; Ricciuto, D. M.; Sargsyan, K.; Najm, H. N.; Debusschere, B.; Thornton, P. E.

2013-12-01

We present uncertainty quantification results for a process-based ecosystem carbon model. The model employs 18 parameters and is driven by meteorological data corresponding to years 1992-2006 at the Harvard Forest site. Daily Net Ecosystem Exchange (NEE) observations were available to calibrate the model parameters and test the performance of the model. Posterior distributions show good predictive capabilities for the calibrated model. A global sensitivity analysis was first performed to determine the important model parameters based on their contribution to the variance of NEE. We then proceed to calibrate the model parameters in a Bayesian framework. The daily discrepancies between measured and predicted NEE values were modeled as independent and identically distributed Gaussians with prescribed daily variance according to the recorded instrument error. All model parameters were assumed to have uninformative priors with bounds set according to expert opinion. The global sensitivity results show that the rate of leaf fall (LEAFALL) is responsible for approximately 25% of the total variance in the average NEE for 1992-2005. A set of 4 other parameters, Nitrogen use efficiency (NUE), base rate for maintenance respiration (BR_MR), growth respiration fraction (RG_FRAC), and allocation to plant stem pool (ASTEM) contribute between 5% and 12% to the variance in average NEE, while the rest of the parameters have smaller contributions. The posterior distributions, sampled with a Markov Chain Monte Carlo algorithm, exhibit significant correlations between model parameters. However LEAFALL, the most important parameter for the average NEE, is not informed by the observational data, while less important parameters show significant updates between their prior and posterior densities. The Fisher information matrix values, indicating which parameters are most informed by the experimental observations, are examined to augment the comparison between the calibration and global sensitivity analysis results.

Income reliably predicts daily sadness, but not happiness: A replication and extension of Kushlev, Dunn, & Lucas (2015)

PubMed Central

Hudson, Nathan W.; Lucas, Richard E.; Donnellan, M. Brent; Kushlev, Kostadin

2017-01-01

Kushlev, Dunn, and Lucas (2015) found that income predicts less daily sadness—but not greater happiness—among Americans. The present study used longitudinal data from an approximately representative German sample to replicate and extend these findings. Our results largely replicated Kushlev and colleagues’: income predicted less daily sadness (albeit with a smaller effect size), but was unrelated to happiness. Moreover, the association between income and sadness could not be explained by demographics, stress, or daily time-use. Extending Kushlev and colleagues’ findings, new analyses indicated that only between-persons variance in income (but not within-persons variance) predicted daily sadness—perhaps because there was relatively little within-persons variance in income. Finally, income predicted less daily sadness and worry, but not less anger or frustration—potentially suggesting that income predicts less “internalizing” but not less “externalizing” negative emotions. Together, our study and Kushlev and colleagues’ provide evidence that income robustly predicts select daily negative emotions—but not positive ones. PMID:29250303

The Role of Habit and Perceived Control on Health Behavior among Pregnant Women.

PubMed

Mullan, Barbara; Henderson, Joanna; Kothe, Emily; Allom, Vanessa; Orbell, Sheina; Hamilton, Kyra

2016-05-01

Many pregnant women do not adhere to physical activity and dietary recommendations. Research investigating what psychological processes might predict physical activity and healthy eating (fruit and vegetable consumption) during pregnancy is scant. We explored the role of intention, habit, and perceived behavioral control as predictors of physical activity and healthy eating. Pregnant women (N = 195, Mage = 30.17, SDage = 4.46) completed questionnaires at 2 time points. At Time 1, participants completed measures of intention, habit, and perceived behavioral control. At Time 2, participants reported on their behavior (physical activity and healthy eating) within the intervening week. Regression analysis determined whether Time 1 variables predicted behavior at Time 2. Interaction terms also were tested. Final regression models indicated that only intention and habit explained significant variance in physical activity, whereas habit and the interaction between intention and habit explained significant variance in healthy eating. Simple slopes analysis indicated that the relationship between intention and healthy eating behavior was only significant at high levels of habit. Findings highlight the influence of habit on behavior and suggest that automaticity interventions may be useful in changing health behaviors during pregnancy.

Health Care Waste Segregation Behavior among Health Workers in Uganda: An Application of the Theory of Planned Behavior.

PubMed

Akulume, Martha; Kiwanuka, Suzanne N

2016-01-01

Objective . The goal of this study was to assess the appropriateness of the theory of planned behavior in predicting health care waste segregation behaviors and to examine the factors that influence waste segregation behaviors. Methodology . One hundred and sixty-three health workers completed a self-administered questionnaire in a cross-sectional survey that examined the theory of planned behavior constructs (attitudes, subjective norms, perceived behavioral control, and intention) and external variables (sociodemographic factors, personal characteristics, organizational characteristics, professional characteristics, and moral obligation). Results . For their most recent client 21.5% of the health workers reported that they most definitely segregated health care waste while 5.5% did not segregate. All the theory of planned behavior constructs were significant predictors of health workers' segregation behavior, but intention emerged as the strongest and most significant ( r = 0.524, P < 0.001). The theory of planned behavior model explained 52.5% of the variance in health workers' segregation behavior. When external variables were added, the new model explained 66.7% of the variance in behavior. Conclusion . Generally, health workers' health care waste segregation behavior was high. The theory of planned behavior significantly predicted health workers' health care waste segregation behaviors.

Decomposing the relation between Rapid Automatized Naming (RAN) and reading ability.

PubMed

Arnell, Karen M; Joanisse, Marc F; Klein, Raymond M; Busseri, Michael A; Tannock, Rosemary

2009-09-01

The Rapid Automatized Naming (RAN) test involves rapidly naming sequences of items presented in a visual array. RAN has generated considerable interest because RAN performance predicts reading achievement. This study sought to determine what elements of RAN are responsible for the shared variance between RAN and reading performance using a series of cognitive tasks and a latent variable modelling approach. Participants performed RAN measures, a test of reading speed and comprehension, and six tasks, which tapped various hypothesised components of the RAN. RAN shared 10% of the variance with reading comprehension and 17% with reading rate. Together, the decomposition tasks explained 52% and 39% of the variance shared between RAN and reading comprehension and between RAN and reading rate, respectively. Significant predictors suggested that working memory encoding underlies part of the relationship between RAN and reading ability.

Predictive factors for somatization in a trauma sample

PubMed Central

2009-01-01

Background Unexplained somatic symptoms are common among trauma survivors. The relationship between trauma and somatization appears to be mediated by posttraumatic stress disorder (PTSD). However, only few studies have focused on what other psychological risk factors may predispose a trauma victim towards developing somatoform symptoms. Methods The present paper examines the predictive value of PTSD severity, dissociation, negative affectivity, depression, anxiety, and feeling incompetent on somatization in a Danish sample of 169 adult men and women who were affected by a series of explosions in a firework factory settled in a residential area. Results Negative affectivity and feelings of incompetence significantly predicted somatization, explaining 42% of the variance. PTSD was significant until negative affectivity was controlled for. Conclusion Negative affectivity and feelings of incompetence significantly predicted somatization in the trauma sample whereas dissociation, depression, and anxiety were not associated with degree of somatization. PTSD as a risk factor was mediated by negative affectivity. PMID:19126224

Jensen's Inequality Predicts Effects of Environmental Variation

Treesearch

Jonathan J. Ruel; Matthew P. Ayres

1999-01-01

Many biologists now recognize that environmental variance can exert important effects on patterns and processes in nature that are independent of average conditions. Jenson's inequality is a mathematical proof that is seldom mentioned in the ecological literature but which provides a powerful tool for predicting some direct effects of environmental variance in...

Psychosocial Adjustment in Siblings of Children with War-Related Injuries

ERIC Educational Resources Information Center

Khamis, Vivian

2013-01-01

The study assessed the prevalence and predictors of post-traumatic symptomatology and emotional and behavioral difficulties in siblings of children who incurred war-related injuries. It was predicted that injury severity, gender and attributional style would account for a significant amount of the variance in post-traumatic stress symptoms and…

The Importance of Intrinsic Motivation for High and Low Ability Readers' Reading Comprehension Performance

ERIC Educational Resources Information Center

Logan, Sarah; Medford, Emma; Hughes, Naomi

2011-01-01

The study examined how cognitive and motivational factors predicted reading skill and whether intrinsic reading motivation would explain significantly more variance in low ability readers' reading performance. One hundred and eleven children (aged 9-11) completed assessments of reading comprehension skill, verbal IQ, decoding skill and intrinsic…

On the Contribution of Kindergarten Writing to Grade 1 Literacy: A Longitudinal Study in Hebrew.

ERIC Educational Resources Information Center

Shatil, Evelyn; Share, David L.; Levin, Iris

2000-01-01

This longitudinal study examined the relationship between kindergarten word writing and Grade 1 literacy in a large sample of Israeli children. Kindergarten writing significantly predicted variance in all three measures of Grade 1 literacy, even after controlling for intelligence. Also examined the role of alphabetic skills and socioliteracy…

Individual differences in emotion word processing: A diffusion model analysis.

PubMed

Mueller, Christina J; Kuchinke, Lars

2016-06-01

The exploratory study investigated individual differences in implicit processing of emotional words in a lexical decision task. A processing advantage for positive words was observed, and differences between happy and fear-related words in response times were predicted by individual differences in specific variables of emotion processing: Whereas more pronounced goal-directed behavior was related to a specific slowdown in processing of fear-related words, the rate of spontaneous eye blinks (indexing brain dopamine levels) was associated with a processing advantage of happy words. Estimating diffusion model parameters revealed that the drift rate (rate of information accumulation) captures unique variance of processing differences between happy and fear-related words, with highest drift rates observed for happy words. Overall emotion recognition ability predicted individual differences in drift rates between happy and fear-related words. The findings emphasize that a significant amount of variance in emotion processing is explained by individual differences in behavioral data.

Students' perceptions of communication ease and engagement. How they relate to academic success.

PubMed

Long, G; Stinson, M S; Braeges, J

1991-12-01

The extent to which students' self-perceptions of communication ease and engagement relate to their academic achievement was assessed in a study of 95 high school students enrolled in a large urban school for the deaf. Four dimensions of classroom communication were measured: students' understanding of teachers, students' understanding of peers, and positive and negative feelings about communication at school. Engagement, the extent students report being excited and actively involved in the classroom, predicted only teacher-assigned grades when the variance of background variables such as residual hearing and IQ was removed. However, communication ease made a significant contribution to the prediction of the three standardized achievement test scores, as well as grades, when background variance was removed. The results suggest that students are more likely to learn if they perceive themselves as being effective in communicating and have positive feelings about the communication that occurs.

Clinical Performance and Admission Variables as Predictors of Passage of the National Physical Therapy Examination.

PubMed

Meiners, Kelly M; Rush, Douglas K

2017-01-01

Prior studies have explored variables that had predictive relationships with National Physical Therapy Examination (NPTE) score or NPTE failure. The purpose of this study was to explore whether certain variables were predictive of test-takers' first-time score on the NPTE. The population consisted of 134 students who graduated from the university's Professional DPT Program in 2012 to 2014. This quantitative study used a retrospective design. Two separate data analyses were conducted. First, hierarchical linear multiple regression (HMR) analysis was performed to determine which variables were predictive of first-time NPTE score. Second, a correlation analysis was performed on all 18 Physical Therapy Clinical Performance Instrument (PT CPI) 2006 category scores obtained during the first long-term clinical rotation, overall PT CPI 2006 score, and NPTE passage. With all variables entered, the HMR model predicted 39% of the variance seen in NPTE scores. The HMR results showed that physical therapy program first-year GPA (1PTGPA) was the strongest predictor and explained 24% of the variance in NPTE scores (b=0.572, p<0.001). The correlational analysis found no statistically significant correlation between the 18 PT CPI 2006 category scores, overall PT CPI 2006 score, and NPTE passage. As 1PTGPA had the most significant contribution to prediction of NPTE scores, programs need to monitor first-year students who display academic difficulty. PT CPI version 2006 scores were significantly correlated with each other, but not with NPTE score or NPTE passage. Both tools measure many of the same professional requirements but use different modes of assessment, and they may be considered complementary tools to gain a full picture of both the student's ability and skills.

Do motor ability and handwriting kinematic measures predict organizational ability among children with Developmental Coordination Disorders?

PubMed

Rosenblum, Sara

2015-10-01

Children with Developmental Coordination Disorders (DCD) exhibit deficient daily performance concealed in their perception-action mechanism. The aim of this study was to analyze behavior organization of children with DCD, in varied tasks that require generating and monitoring mental representations related to space and time inputs/requirements, for achieving better insight about their perception-action mechanism. Participants included 42 children aged 7-10, half of whom were defined with DCD and half were typically developing (TD). The children were matched for age, gender and school. They were evaluated using the Movement-ABC and performed three handwriting tasks on an electronic tablet that is part of a computerized system (ComPET - Computerized Penmanship Evaluation Tool). In addition, their teachers completed the Questionnaire for Assessing Students' Organizational Abilities-Teachers (QASOA-T) to assess the children's daily organizational ability. Significant group differences (DCD versus controls) were found for all handwriting kinematic measures across the three handwriting tasks and for the children's organizational abilities. Motor ability predicted a considerable percentage of the variance of the kinematic handwriting measures (30-37%), as well as a high percentage of the variance of their organizational abilities (67%). The coefficient of variance of the pen tilt added an additional 3% to the prediction of their organizational abilities. The results of this study exhibited deficient ability among children with DCD in organizing their behavior in varied real-world tasks requiring generation and monitoring representation related to space and time. The significance of the results to understanding the performance mechanism and implication to the clinical field are discussed. Copyright © 2015 Elsevier B.V. All rights reserved.

Relationships between reef fish communities and remotely sensed rugosity measurements in Biscayne National Park, Florida, USA

USGS Publications Warehouse

Kuffner, Ilsa B.; Brock, John C.; Grober-Dunsmore, Rikki; Bonito, Victor E.; Hickey, T. Donald; Wright, C. Wayne

2007-01-01

The realization that coral reef ecosystem management must occur across multiple spatial scales and habitat types has led scientists and resource managers to seek variables that are easily measured over large areas and correlate well with reef resources. Here we investigate the utility of new technology in airborne laser surveying (NASA Experimental Advanced Airborne Research Lidar (EAARL)) in assessing topographical complexity (rugosity) to predict reef fish community structure on shallow (n = 10–13 per reef). Rugosity at each station was assessed in situ by divers using the traditional chain-transect method (10-m scale), and remotely using the EAARL submarine topography data at multiple spatial scales (2, 5, and 10 m). The rugosity and biological datasets were analyzed together to elucidate the predictive power of EAARL rugosity in describing the variance in reef fish community variables and to assess the correlation between chain-transect and EAARL rugosity. EAARL rugosity was not well correlated with chain-transect rugosity, or with species richness of fishes (although statistically significant, the amount of variance explained by the model was very low). Variance in reef fish community attributes was better explained in reef-by-reef variability than by physical variables. However, once the reef-by-reef variability was taken into account in a two-way analysis of variance, the importance of rugosity could be seen on individual reefs. Fish species richness and abundance were statistically higher at high rugosity stations compared to medium and low rugosity stations, as predicted by prior ecological research. The EAARL shows promise as an important mapping tool for reef resource managers as they strive to inventory and protect coral reef resources.

The effects of initial participation motivations on learning engagement in transition training for future general practitioners in rural China: perceived deterrents as mediator

PubMed Central

Cui, Guan-yu; Yao, Mei-lin; Zhang, Xia; Guo, Yan-kui; Li, Hui-min; Yao, Xiu-ping

2016-01-01

Background For the shortage of high-quality general practitioners (GPs) in China's rural areas, Chinese government has taken steps to encourage rural specialists to participate in transition training for future GPs. Specialists’ initial participation motivations and their perceived deterrents during training may play important roles for their learning engagement in the transition training. This study aimed at revealing the relationships among the variables of initial participation motivations, perceived deterrents in training, and learning engagement. Methods A questionnaire survey was used in this study. A total of 156 rural specialists who participated in transition training for future GPs filled out the questionnaire, which consisted of the measurements of initial participation motivations, perceived deterrents, and learning engagement in training. The data about specialists’ demographic variables were collected at the same time. Results The variance of initial escape/stimulations motivation significantly predicted the variance of learning engagement through the full mediating role of perceived deterrents in training. In addition, initial educational preparation motivations predicted the variance of learning engagement directly. Conclusions Specialists’ initial participation motivations and perceived deterrents in training played important roles for learning engagement in the transition training. PMID:27340086

Suicide proneness in college students: relationships with gender, procrastination, and achievement motivation.

PubMed

Klibert, Jeffrey; Langhinrichsen-Rohling, Jennifer; Luna, Amy; Robichaux, Michelle

2011-08-01

This study examined the relationships between 2 academic dispositions (i.e., procrastination and achievement motivation) and 2 indices of suicidal proneness in college women and men. The degree these 2 academic dispositions could predict unique variance in suicide proneness scores, above and beyond the influence of depression and self-esteem was also examined for each gender. Participants included 475 (336 women, 139 men) undergraduates from a southeastern university. For both genders, procrastination and achievement motivation were significantly correlated at the univarate level with the suicide proneness indices. However, for college women, but not men, procrastination significantly accounted for unique amounts of variance in both suicide indices above and beyond the influence of depression and self-esteem. Implications for suicide intervention efforts directed toward college women and men are offered.

Value of MR histogram analyses for prediction of microvascular invasion of hepatocellular carcinoma.

PubMed

Huang, Ya-Qin; Liang, He-Yue; Yang, Zhao-Xia; Ding, Ying; Zeng, Meng-Su; Rao, Sheng-Xiang

2016-06-01

The objective is to explore the value of preoperative magnetic resonance (MR) histogram analyses in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC).Fifty-one patients with histologically confirmed HCC who underwent diffusion-weighted and contrast-enhanced MR imaging were included. Histogram analyses were performed and mean, variance, skewness, kurtosis, 1th, 10th, 50th, 90th, and 99th percentiles were derived. Quantitative histogram parameters were compared between HCCs with and without MVI. Receiver operating characteristics (ROC) analyses were generated to compare the diagnostic performance of tumor size, histogram analyses of apparent diffusion coefficient (ADC) maps, and MR enhancement.The mean, 1th, 10th, and 50th percentiles of ADC maps, and the mean, variance. 1th, 10th, 50th, 90th, and 99th percentiles of the portal venous phase (PVP) images were significantly different between the groups with and without MVI (P <0.05), with area under the ROC curves (AUCs) of 0.66 to 0.74 for ADC and 0.76 to 0.88 for PVP. The largest AUC of PVP (1th percentile) showed significantly higher accuracy compared with that of arterial phase (AP) or tumor size (P <0.001).MR histogram analyses-in particular for 1th percentile for PVP images-held promise for prediction of MVI of HCC.

Relation between Peak Power Output in Sprint Cycling and Maximum Voluntary Isometric Torque Production.

PubMed

Kordi, Mehdi; Goodall, Stuart; Barratt, Paul; Rowley, Nicola; Leeder, Jonathan; Howatson, Glyn

2017-08-01

From a cycling paradigm, little has been done to understand the relationships between maximal isometric strength of different single joint lower body muscle groups and their relation with, and ability to predict PPO and how they compare to an isometric cycling specific task. The aim of this study was to establish relationships between maximal voluntary torque production from isometric single-joint and cycling specific tasks and assess their ability to predict PPO. Twenty male trained cyclists participated in this study. Peak torque was measured by performing maximum voluntary contractions (MVC) of knee extensors, knee flexors, dorsi flexors and hip extensors whilst instrumented cranks measured isometric peak torque from MVC when participants were in their cycling specific position (ISOCYC). A stepwise regression showed that peak torque of the knee extensors was the only significant predictor of PPO when using SJD and accounted for 47% of the variance. However, when compared to ISOCYC, the only significant predictor of PPO was ISOCYC, which accounted for 77% of the variance. This suggests that peak torque of the knee extensors was the best single-joint predictor of PPO in sprint cycling. Furthermore, a stronger prediction can be made from a task specific isometric task. Copyright © 2017 Elsevier Ltd. All rights reserved.

Breeding Jatropha curcas by genomic selection: A pilot assessment of the accuracy of predictive models.

PubMed

Azevedo Peixoto, Leonardo de; Laviola, Bruno Galvêas; Alves, Alexandre Alonso; Rosado, Tatiana Barbosa; Bhering, Leonardo Lopes

2017-01-01

Genomic wide selection is a promising approach for improving the selection accuracy in plant breeding, particularly in species with long life cycles, such as Jatropha. Therefore, the objectives of this study were to estimate the genetic parameters for grain yield (GY) and the weight of 100 seeds (W100S) using restricted maximum likelihood (REML); to compare the performance of GWS methods to predict GY and W100S; and to estimate how many markers are needed to train the GWS model to obtain the maximum accuracy. Eight GWS models were compared in terms of predictive ability. The impact that the marker density had on the predictive ability was investigated using a varying number of markers, from 2 to 1,248. Because the genetic variance between evaluated genotypes was significant, it was possible to obtain selection gain. All of the GWS methods tested in this study can be used to predict GY and W100S in Jatropha. A training model fitted using 1,000 and 800 markers is sufficient to capture the maximum genetic variance and, consequently, maximum prediction ability of GY and W100S, respectively. This study demonstrated the applicability of genome-wide prediction to identify useful genetic sources of GY and W100S for Jatropha breeding. Further research is needed to confirm the applicability of the proposed approach to other complex traits.

Genetic polymorphisms to predict gains in maximal O2 uptake and knee peak torque after a high intensity training program in humans.

PubMed

Yoo, Jinho; Kim, Bo-Hyung; Kim, Soo-Hwan; Kim, Yangseok; Yim, Sung-Vin

2016-05-01

The study aimed to identify single nucleotide polymorphisms (SNPs) that significantly influenced the level of improvement of two kinds of training responses, including maximal O2 uptake (V'O2max) and knee peak torque of healthy adults participating in the high intensity training (HIT) program. The study also aimed to use these SNPs to develop prediction models for individual training responses. 79 Healthy volunteers participated in the HIT program. A genome-wide association study, based on 2,391,739 SNPs, was performed to identify SNPs that were significantly associated with gains in V'O2max and knee peak torque, following 9 weeks of the HIT program. To predict two training responses, two independent SNPs sets were determined using linear regression and iterative binary logistic regression analysis. False discovery rate analysis and permutation tests were performed to avoid false-positive findings. To predict gains in V'O2max, 7 SNPs were identified. These SNPs accounted for 26.0 % of the variance in the increment of V'O2max, and discriminated the subjects into three subgroups, non-responders, medium responders, and high responders, with prediction accuracy of 86.1 %. For the knee peak torque, 6 SNPs were identified, and accounted for 27.5 % of the variance in the increment of knee peak torque. The prediction accuracy discriminating the subjects into the three subgroups was estimated as 77.2 %. Novel SNPs found in this study could explain, and predict inter-individual variability in gains of V'O2max, and knee peak torque. Furthermore, with these genetic markers, a methodology suggested in this study provides a sound approach for the personalized training program.

Situation awareness measures for simulated submarine track management.

PubMed

Loft, Shayne; Bowden, Vanessa; Braithwaite, Janelle; Morrell, Daniel B; Huf, Samuel; Durso, Francis T

2015-03-01

The aim of this study was to examine whether the Situation Present Assessment Method (SPAM) and the Situation Awareness Global Assessment Technique (SAGAT) predict incremental variance in performance on a simulated submarine track management task and to measure the potential disruptive effect of these situation awareness (SA) measures. Submarine track managers use various displays to localize and track contacts detected by own-ship sensors. The measurement of SA is crucial for designing effective submarine display interfaces and training programs. Participants monitored a tactical display and sonar bearing-history display to track the cumulative behaviors of contacts in relationship to own-ship position and landmarks. SPAM (or SAGAT) and the Air Traffic Workload Input Technique (ATWIT) were administered during each scenario, and the NASA Task Load Index (NASA-TLX) and Situation Awareness Rating Technique were administered postscenario. SPAM and SAGAT predicted variance in performance after controlling for subjective measures of SA and workload, and SA for past information was a stronger predictor than SA for current/future information. The NASA-TLX predicted performance on some tasks. Only SAGAT predicted variance in performance on all three tasks but marginally increased subjective workload. SPAM, SAGAT, and the NASA-TLX can predict unique variance in submarine track management performance. SAGAT marginally increased subjective workload, but this increase did not lead to any performance decrement. Defense researchers have identified SPAM as an alternative to SAGAT because it would not require field exercises involving submarines to be paused. SPAM was not disruptive, but it is potentially problematic that SPAM did not predict variance in all three performance tasks. © 2014, Human Factors and Ergonomics Society.

Transforming RNA-Seq data to improve the performance of prognostic gene signatures.

PubMed

Zwiener, Isabella; Frisch, Barbara; Binder, Harald

2014-01-01

Gene expression measurements have successfully been used for building prognostic signatures, i.e for identifying a short list of important genes that can predict patient outcome. Mostly microarray measurements have been considered, and there is little advice available for building multivariable risk prediction models from RNA-Seq data. We specifically consider penalized regression techniques, such as the lasso and componentwise boosting, which can simultaneously consider all measurements and provide both, multivariable regression models for prediction and automated variable selection. However, they might be affected by the typical skewness, mean-variance-dependency or extreme values of RNA-Seq covariates and therefore could benefit from transformations of the latter. In an analytical part, we highlight preferential selection of covariates with large variances, which is problematic due to the mean-variance dependency of RNA-Seq data. In a simulation study, we compare different transformations of RNA-Seq data for potentially improving detection of important genes. Specifically, we consider standardization, the log transformation, a variance-stabilizing transformation, the Box-Cox transformation, and rank-based transformations. In addition, the prediction performance for real data from patients with kidney cancer and acute myeloid leukemia is considered. We show that signature size, identification performance, and prediction performance critically depend on the choice of a suitable transformation. Rank-based transformations perform well in all scenarios and can even outperform complex variance-stabilizing approaches. Generally, the results illustrate that the distribution and potential transformations of RNA-Seq data need to be considered as a critical step when building risk prediction models by penalized regression techniques.

Transforming RNA-Seq Data to Improve the Performance of Prognostic Gene Signatures

PubMed Central

Zwiener, Isabella; Frisch, Barbara; Binder, Harald

2014-01-01

Gene expression measurements have successfully been used for building prognostic signatures, i.e for identifying a short list of important genes that can predict patient outcome. Mostly microarray measurements have been considered, and there is little advice available for building multivariable risk prediction models from RNA-Seq data. We specifically consider penalized regression techniques, such as the lasso and componentwise boosting, which can simultaneously consider all measurements and provide both, multivariable regression models for prediction and automated variable selection. However, they might be affected by the typical skewness, mean-variance-dependency or extreme values of RNA-Seq covariates and therefore could benefit from transformations of the latter. In an analytical part, we highlight preferential selection of covariates with large variances, which is problematic due to the mean-variance dependency of RNA-Seq data. In a simulation study, we compare different transformations of RNA-Seq data for potentially improving detection of important genes. Specifically, we consider standardization, the log transformation, a variance-stabilizing transformation, the Box-Cox transformation, and rank-based transformations. In addition, the prediction performance for real data from patients with kidney cancer and acute myeloid leukemia is considered. We show that signature size, identification performance, and prediction performance critically depend on the choice of a suitable transformation. Rank-based transformations perform well in all scenarios and can even outperform complex variance-stabilizing approaches. Generally, the results illustrate that the distribution and potential transformations of RNA-Seq data need to be considered as a critical step when building risk prediction models by penalized regression techniques. PMID:24416353

Suicidal behavior in obsessive-compulsive disorder.

PubMed

Kamath, Prakash; Reddy, Y C Janardhan; Kandavel, Thennarasu

2007-11-01

There are limited data on suicidal behavior in obsessive-compulsive disorder (OCD). This study examines suicidal behavior and its clinical correlates in OCD subjects. One hundred consecutive DSM-IV OCD subjects attending the specialty OCD clinic and the inpatient services of a major psychiatric hospital in India from November 1, 2003, to October 31, 2004, formed the sample of this study. Subjects were assessed systematically by using structured interviews and various rating scales. The Scale for Suicide Ideation-worst ever (lifetime) and -current measured suicidal ideation. The 24-item Hamilton Rating Scale for Depression (HAM-D) measured severity of depression, and the Beck Hopelessness Scale (BHS) measured hopelessness. We performed assessments at study entry. We employed binary logistic regression (Wald) forward stepwise analysis for prediction of suicidal ideation and suicide attempt, and we used structural equation modeling for identifying the potential factors contributing to suicidal ideation. The rates of suicidal ideation, worst ever and current, were 59% and 28%, respectively. History of suicide attempt was reported in 27% of the subjects. For past suicide attempt, worst ever suicidal ideation (p < .001) was the only significant predictor, with an overall prediction of 89%, and accounted for 60% of the variance. For worst ever suicidal ideation, major depression (p = .043), HAM-D score (p = .013), BHS score (p = .011), and history of attempt (p = .009) were significant predictors, with an overall prediction of 82% and variance of 56%. Somewhat similar predictors emerged as significant for current suicidal ideators, with an overall prediction of 85% and variance of 50%. In the structural equation model, too, presence of depression and high BHS score contributed to suicidal ideation. OCD is associated with a high risk for suicidal behavior. Depression and hopelessness are the major correlates of suicidal behavior. It is vital that patients with OCD undergo detailed assessment for suicide risk and associated depression. Aggressive treatment of depression may be warranted to modify the risk for suicide. Future studies should examine suicidal behavior in a prospective design in larger samples to examine if severity of OCD and treatment nonresponse contribute to suicide risk.

Working Memory and Speech Comprehension in Older Adults With Hearing Impairment.

PubMed

Nagaraj, Naveen K

2017-10-17

This study examined the relationship between working memory (WM) and speech comprehension in older adults with hearing impairment (HI). It was hypothesized that WM would explain significant variance in speech comprehension measured in multitalker babble (MTB). Twenty-four older (59-73 years) adults with sensorineural HI participated. WM capacity (WMC) was measured using 3 complex span tasks. Speech comprehension was assessed using multiple passages, and speech identification ability was measured using recall of sentence final-word and key words. Speech measures were performed in quiet and in the presence of MTB at + 5 dB signal-to-noise ratio. Results suggested that participants' speech identification was poorer in MTB, but their ability to comprehend discourse in MTB was at least as good as in quiet. WMC did not explain significant variance in speech comprehension before and after controlling for age and audibility. However, WMC explained significant variance in low-context sentence key words identification in MTB. These results suggest that WMC plays an important role in identifying low-context sentences in MTB, but not when comprehending semantically rich discourse passages. In general, data did not support individual variability in WMC as a factor that predicts speech comprehension ability in older adults with HI.

Generalized Variance Function Applications in Forestry

Treesearch

James Alegria; Charles T. Scott; Charles T. Scott

1991-01-01

Adequately predicting the sampling errors of tabular data can reduce printing costs by eliminating the need to publish separate sampling error tables. Two generalized variance functions (GVFs) found in the literature and three GVFs derived for this study were evaluated for their ability to predict the sampling error of tabular forestry estimates. The recommended GVFs...

Performance of chromatographic systems to model soil-water sorption.

PubMed

Hidalgo-Rodríguez, Marta; Fuguet, Elisabet; Ràfols, Clara; Rosés, Martí

2012-08-24

A systematic approach for evaluating the goodness of chromatographic systems to model the sorption of neutral organic compounds by soil from water is presented in this work. It is based on the examination of the three sources of error that determine the overall variance obtained when soil-water partition coefficients are correlated against chromatographic retention factors: the variance of the soil-water sorption data, the variance of the chromatographic data, and the variance attributed to the dissimilarity between the two systems. These contributions of variance are easily predicted through the characterization of the systems by the solvation parameter model. According to this method, several chromatographic systems besides the reference octanol-water partition system have been selected to test their performance in the emulation of soil-water sorption. The results from the experimental correlations agree with the predicted variances. The high-performance liquid chromatography system based on an immobilized artificial membrane and the micellar electrokinetic chromatography systems of sodium dodecylsulfate and sodium taurocholate provide the most precise correlation models. They have shown to predict well soil-water sorption coefficients of several tested herbicides. Octanol-water partitions and high-performance liquid chromatography measurements using C18 columns are less suited for the estimation of soil-water partition coefficients. Copyright © 2012 Elsevier B.V. All rights reserved.

Testing life history predictions in a long-lived seabird: A population matrix approach with improved parameter estimation

USGS Publications Warehouse

Doherty, P.F.; Schreiber, E.A.; Nichols, J.D.; Hines, J.E.; Link, W.A.; Schenk, G.A.; Schreiber, R.W.

2004-01-01

Life history theory and associated empirical generalizations predict that population growth rate (λ) in long-lived animals should be most sensitive to adult survival; the rates to which λ is most sensitive should be those with the smallest temporal variances; and stochastic environmental events should most affect the rates to which λ is least sensitive. To date, most analyses attempting to examine these predictions have been inadequate, their validity being called into question by problems in estimating parameters, problems in estimating the variability of parameters, and problems in measuring population sensitivities to parameters. We use improved methodologies in these three areas and test these life-history predictions in a population of red-tailed tropicbirds (Phaethon rubricauda). We support our first prediction that λ is most sensitive to survival rates. However the support for the second prediction that these rates have the smallest temporal variance was equivocal. Previous support for the second prediction may be an artifact of a high survival estimate near the upper boundary of 1 and not a result of natural selection canalizing variances alone. We did not support our third prediction that effects of environmental stochasticity (El Niño) would most likely be detected in vital rates to which λ was least sensitive and which are thought to have high temporal variances. Comparative data-sets on other seabirds, within and among orders, and in other locations, are needed to understand these environmental effects.

Effect of correlated observation error on parameters, predictions, and uncertainty

USGS Publications Warehouse

Tiedeman, Claire; Green, Christopher T.

2013-01-01

Correlations among observation errors are typically omitted when calculating observation weights for model calibration by inverse methods. We explore the effects of omitting these correlations on estimates of parameters, predictions, and uncertainties. First, we develop a new analytical expression for the difference in parameter variance estimated with and without error correlations for a simple one-parameter two-observation inverse model. Results indicate that omitting error correlations from both the weight matrix and the variance calculation can either increase or decrease the parameter variance, depending on the values of error correlation (ρ) and the ratio of dimensionless scaled sensitivities (rdss). For small ρ, the difference in variance is always small, but for large ρ, the difference varies widely depending on the sign and magnitude of rdss. Next, we consider a groundwater reactive transport model of denitrification with four parameters and correlated geochemical observation errors that are computed by an error-propagation approach that is new for hydrogeologic studies. We compare parameter estimates, predictions, and uncertainties obtained with and without the error correlations. Omitting the correlations modestly to substantially changes parameter estimates, and causes both increases and decreases of parameter variances, consistent with the analytical expression. Differences in predictions for the models calibrated with and without error correlations can be greater than parameter differences when both are considered relative to their respective confidence intervals. These results indicate that including observation error correlations in weighting for nonlinear regression can have important effects on parameter estimates, predictions, and their respective uncertainties.

Applying the Expectancy-Value Model to understand health values.

PubMed

Zhang, Xu-Hao; Xie, Feng; Wee, Hwee-Lin; Thumboo, Julian; Li, Shu-Chuen

2008-03-01

Expectancy-Value Model (EVM) is the most structured model in psychology to predict attitudes by measuring attitudinal attributes (AAs) and relevant external variables. Because health value could be categorized as attitude, we aimed to apply EVM to explore its usefulness in explaining variances in health values and investigate underlying factors. Focus group discussion was carried out to identify the most common and significant AAs toward 5 different health states (coded as 11111, 11121, 21221, 32323, and 33333 in EuroQol Five-Dimension (EQ-5D) descriptive system). AAs were measured in a sum of multiplications of subjective probability (expectancy) and perceived value of attributes with 7-point Likert scales. Health values were measured using visual analog scales (VAS, range 0-1). External variables (age, sex, ethnicity, education, housing, marital status, and concurrent chronic diseases) were also incorporated into survey questionnaire distributed by convenience sampling among eligible respondents. Univariate analyses were used to identify external variables causing significant differences in VAS. Multiple linear regression model (MLR) and hierarchical regression model were used to investigate the explanatory power of AAs and possible significant external variable(s) separately or in combination, for each individual health state and a mixed scenario of five states, respectively. Four AAs were identified, namely, "worsening your quality of life in terms of health" (WQoL), "adding a burden to your family" (BTF), "making you less independent" (MLI) and "unable to work or study" (UWS). Data were analyzed based on 232 respondents (mean [SD] age: 27.7 [15.07] years, 49.1% female). Health values varied significantly across 5 health states, ranging from 0.12 (33333) to 0.97 (11111). With no significant external variables identified, EVM explained up to 62% of the variances in health values across 5 health states. The explanatory power of 4 AAs were found to be between 13% and 28% in separate MLR models (P < 0.05). When data were analyzed for each health state, variances in health values became small and explanatory power of EVM was reduced to a range between 8% and 23%. EVM was useful in explaining variances of health values and predicting important factors. Its power to explain small variances might be restricted due to limitations of 7-point Likert scale to measure AAs accurately. With further improvement and validation of a compatible continuous scale for more accurate measurement, EVM is expected to explain health values to a larger extent.

Predicting the Cost per Flying Hour for the F-16 Using Programmatic and Operational Variables

DTIC Science & Technology

2005-06-01

constant variance assumption is accomplished using the Breusch - Pagan test . This is accomplished and the results are listed in Table 12. Figures 19...and 20 follow and add to the discussion by plotting the residuals by predicted for both models. 52 Table 12: Breusch - Pagan Constant Variance Test ...Model A 13844455 6.97E+11 5 74 9.96 0.0764 Model B 74954796 8.69E+12 5 151 17.63 0.00344 Breusch - Pagan Test for Constant Variance -1000 -500 0 500

Improvement of Prediction Ability for Genomic Selection of Dairy Cattle by Including Dominance Effects

PubMed Central

Sun, Chuanyu; VanRaden, Paul M.; Cole, John B.; O'Connell, Jeffrey R.

2014-01-01

Dominance may be an important source of non-additive genetic variance for many traits of dairy cattle. However, nearly all prediction models for dairy cattle have included only additive effects because of the limited number of cows with both genotypes and phenotypes. The role of dominance in the Holstein and Jersey breeds was investigated for eight traits: milk, fat, and protein yields; productive life; daughter pregnancy rate; somatic cell score; fat percent and protein percent. Additive and dominance variance components were estimated and then used to estimate additive and dominance effects of single nucleotide polymorphisms (SNPs). The predictive abilities of three models with both additive and dominance effects and a model with additive effects only were assessed using ten-fold cross-validation. One procedure estimated dominance values, and another estimated dominance deviations; calculation of the dominance relationship matrix was different for the two methods. The third approach enlarged the dataset by including cows with genotype probabilities derived using genotyped ancestors. For yield traits, dominance variance accounted for 5 and 7% of total variance for Holsteins and Jerseys, respectively; using dominance deviations resulted in smaller dominance and larger additive variance estimates. For non-yield traits, dominance variances were very small for both breeds. For yield traits, including additive and dominance effects fit the data better than including only additive effects; average correlations between estimated genetic effects and phenotypes showed that prediction accuracy increased when both effects rather than just additive effects were included. No corresponding gains in prediction ability were found for non-yield traits. Including cows with derived genotype probabilities from genotyped ancestors did not improve prediction accuracy. The largest additive effects were located on chromosome 14 near DGAT1 for yield traits for both breeds; those SNPs also showed the largest dominance effects for fat yield (both breeds) as well as for Holstein milk yield. PMID:25084281

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.

Predicting Individual Differences in Placebo Analgesia: Contributions of Brain Activity during Anticipation and Pain Experience

PubMed Central

Wager, Tor D.; Atlas, Lauren Y.; Leotti, Lauren A.; Rilling, James K.

2012-01-01

Recent studies have identified brain correlates of placebo analgesia, but none have assessed how accurately patterns of brain activity can predict individual differences in placebo responses. We reanalyzed data from two fMRI studies of placebo analgesia (N = 47), using patterns of fMRI activity during the anticipation and experience of pain to predict new subjects’ scores on placebo analgesia and placebo-induced changes in pain processing. We used a cross-validated regression procedure, LASSO-PCR, which provided both unbiased estimates of predictive accuracy and interpretable maps of which regions are most important for prediction. Increased anticipatory activity in a frontoparietal network and decreases in a posterior insular/temporal network predicted placebo analgesia. Patterns of anticipatory activity across the cortex predicted a moderate amount of variance in the placebo response (~12% overall, ~40% for study 2 alone), which is substantial considering the multiple likely contributing factors. The most predictive regions were those associated with emotional appraisal, rather than cognitive control or pain processing. During pain, decreases in limbic and paralimbic regions most strongly predicted placebo analgesia. Responses within canonical pain-processing regions explained significant variance in placebo analgesia, but the pattern of effects was inconsistent with widespread decreases in nociceptive processing. Together, the findings suggest that engagement of emotional appraisal circuits drives individual variation in placebo analgesia, rather than early suppression of nociceptive processing. This approach provides a framework that will allow prediction accuracy to increase as new studies provide more precise information for future predictive models. PMID:21228154

Assessing dependency using self-report and indirect measures: examining the significance of discrepancies.

PubMed

Cogswell, Alex; Alloy, Lauren B; Karpinski, Andrew; Grant, David A

2010-07-01

The present study addressed convergence between self-report and indirect approaches to assessing dependency. We were moderately successful in validating an implicit measure, which was found to be reliable, orthogonal to 2 self-report instruments, and predictive of external criteria. This study also examined discrepancies between scores on self-report and implicit measures, and has implications for their significance. The possibility that discrepancies themselves are pathological was not supported, although discrepancies were associated with particular personality profiles. Finally, this study offered additional evidence for the relation between dependency and depressive symptomatology and identified implicit dependency as contributing unique variance in predicting past major depression.

The relationship of extraversion and neuroticism to two measures of assertive behavior.

PubMed

Vestewig, R E; Moss, M K

1976-05-01

One hundred forty-four college students completed the Eysenck Personality Inventory and the Rathus Assertiveness Schedule (RAS) and wrote their behavioral reactions to five scenarios in which an assertive behavior was an appropriate response. Extraversion showed a significant positive correlation with the RAS in both males and females. Neuroticism was negatively correlated with RAS in both sexes. Extraversion and RAS correlated significantly with rated Assertiveness in the scenarios only in the male sample. The RAS predicted variance in Assertiveness beyond that predicted by Extraversion. Overall low correlations of the measures with rated Assertiveness were discussed in terms of the low internal consistency reliability of that scale.

Predictors of Weapon Carrying in Youth Attending Drop-in Centers

ERIC Educational Resources Information Center

Blumberg, Elaine J.; Liles, Sandy; Kelley, Norma J.; Hovell, Melbourne F.; Bousman, Chad A.; Shillington, Audrey M.; Ji, Ming; Clapp, John

2009-01-01

Objective: To test and compare 2 predictive models of weapon carrying in youth (n=308) recruited from 4 drop-in centers in San Diego and Imperial counties. Methods: Both models were based on the Behavioral Ecological Model (BEM). Results: The first and second models significantly explained 39% and 53% of the variance in weapon carrying,…

Estimating Slash Quantity from Standing Loblolly Pine

Treesearch

Dale D. Wade

1969-01-01

No significant difference were found between variances of two prediction equations for estimating loblolly pine crown weight from diameter breast height (d.b.h). One equation was developed from trees on the Georgia Piedmont and the other from tress on the South Carolina Coastal Plain. An equation and table are presented for estimating loblolly pine slash weights from...

Motivational Correlates of Academic Success in an Educational Psychology Course

ERIC Educational Resources Information Center

Herman, William E.

2011-01-01

The variables of class attendance and the institution-wide Early Alert Grading System were employed to predict academic success at the end of the semester. Classroom attendance was found to be statistically and significantly related to final average and accounted for 14-16% of the variance in academic performance. Class attendance was found to…

The Relationship between Parent-Infant Bed Sharing and Marital Satisfaction for Mothers of Infants

ERIC Educational Resources Information Center

Messmer, Rosemary; Miller, Lynn D.; Yu, Christine M.

2012-01-01

This study investigated the relationship between marital satisfaction and time spent bed sharing with infants in a community sample of 81 bed sharing mothers. Time spent bed sharing did not significantly predict variance in marital satisfaction when considering bed sharers as a whole. Moderation analysis, however, showed the interaction between…

Soil respiration and net N mineralization along a climate gradient in Maine

Treesearch

Jeffery A. Simmons; Ivan J. Fernandez; Russell D. Briggs

1996-01-01

Our objective was to determine the influence of temperature and moisture on soil respiration and net N mineralization in northeastern forests. The study consisted of sixteen deciduous stands located along a regional climate gradient within Maine. A significant portion of the variance in net N mineralization (41 percent) and respiration (33 percent) was predicted by...

Student, teacher, and classroom predictors of between-teacher variance of students' teacher-rated behavior.

PubMed

Splett, Joni W; Smith-Millman, Marissa; Raborn, Anthony; Brann, Kristy L; Flaspohler, Paul D; Maras, Melissa A

2018-03-08

The current study examined between-teacher variance in teacher ratings of student behavioral and emotional risk to identify student, teacher and classroom characteristics that predict such differences and can be considered in future research and practice. Data were taken from seven elementary schools in one school district implementing universal screening, including 1,241 students rated by 68 teachers. Students were mostly African America (68.5%) with equal gender (female 50.1%) and grade-level distributions. Teachers, mostly White (76.5%) and female (89.7%), completed both a background survey regarding their professional experiences and demographic characteristics and the Behavior Assessment System for Children (Second Edition) Behavioral and Emotional Screening System-Teacher Form for all students in their class, rating an average of 17.69 students each. Extant student data were provided by the district. Analyses followed multilevel linear model stepwise model-building procedures. We detected a significant amount of variance in teachers' ratings of students' behavioral and emotional risk at both student and teacher/classroom levels with student predictors explaining about 39% of student-level variance and teacher/classroom predictors explaining about 20% of between-teacher differences. The final model fit the data (Akaike information criterion = 8,687.709; pseudo-R2 = 0.544) significantly better than the null model (Akaike information criterion = 9,457.160). Significant predictors included student gender, race ethnicity, academic performance and disciplinary incidents, teacher gender, student-teacher gender interaction, teacher professional development in behavior screening, and classroom academic performance. Future research and practice should interpret teacher-rated universal screening of students' behavioral and emotional risk with consideration of the between-teacher variance unrelated to student behavior detected. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Differential contribution of genomic regions to marked genetic variation and prediction of quantitative traits in broiler chickens.

PubMed

Abdollahi-Arpanahi, Rostam; Morota, Gota; Valente, Bruno D; Kranis, Andreas; Rosa, Guilherme J M; Gianola, Daniel

2016-02-03

Genome-wide association studies in humans have found enrichment of trait-associated single nucleotide polymorphisms (SNPs) in coding regions of the genome and depletion of these in intergenic regions. However, a recent release of the ENCyclopedia of DNA elements showed that ~80 % of the human genome has a biochemical function. Similar studies on the chicken genome are lacking, thus assessing the relative contribution of its genic and non-genic regions to variation is relevant for biological studies and genetic improvement of chicken populations. A dataset including 1351 birds that were genotyped with the 600K Affymetrix platform was used. We partitioned SNPs according to genome annotation data into six classes to characterize the relative contribution of genic and non-genic regions to genetic variation as well as their predictive power using all available quality-filtered SNPs. Target traits were body weight, ultrasound measurement of breast muscle and hen house egg production in broiler chickens. Six genomic regions were considered: intergenic regions, introns, missense, synonymous, 5' and 3' untranslated regions, and regions that are located 5 kb upstream and downstream of coding genes. Genomic relationship matrices were constructed for each genomic region and fitted in the models, separately or simultaneously. Kernel-based ridge regression was used to estimate variance components and assess predictive ability. Contribution of each class of genomic regions to dominance variance was also considered. Variance component estimates indicated that all genomic regions contributed to marked additive genetic variation and that the class of synonymous regions tended to have the greatest contribution. The marked dominance genetic variation explained by each class of genomic regions was similar and negligible (~0.05). In terms of prediction mean-square error, the whole-genome approach showed the best predictive ability. All genic and non-genic regions contributed to phenotypic variation for the three traits studied. Overall, the contribution of additive genetic variance to the total genetic variance was much greater than that of dominance variance. Our results show that all genomic regions are important for the prediction of the targeted traits, and the whole-genome approach was reaffirmed as the best tool for genome-enabled prediction of quantitative traits.

Do drug treatment variables predict cognitive performance in multidrug-treated opioid-dependent patients? A regression analysis study

PubMed Central

2012-01-01

Background Cognitive deficits and multiple psychoactive drug regimens are both common in patients treated for opioid-dependence. Therefore, we examined whether the cognitive performance of patients in opioid-substitution treatment (OST) is associated with their drug treatment variables. Methods Opioid-dependent patients (N = 104) who were treated either with buprenorphine or methadone (n = 52 in both groups) were given attention, working memory, verbal, and visual memory tests after they had been a minimum of six months in treatment. Group-wise results were analysed by analysis of variance. Predictors of cognitive performance were examined by hierarchical regression analysis. Results Buprenorphine-treated patients performed statistically significantly better in a simple reaction time test than methadone-treated ones. No other significant differences between groups in cognitive performance were found. In each OST drug group, approximately 10% of the attention performance could be predicted by drug treatment variables. Use of benzodiazepine medication predicted about 10% of performance variance in working memory. Treatment with more than one other psychoactive drug (than opioid or BZD) and frequent substance abuse during the past month predicted about 20% of verbal memory performance. Conclusions Although this study does not prove a causal relationship between multiple prescription drug use and poor cognitive functioning, the results are relevant for psychosocial recovery, vocational rehabilitation, and psychological treatment of OST patients. Especially for patients with BZD treatment, other treatment options should be actively sought. PMID:23121989

Prediction of activity-related energy expenditure using accelerometer-derived physical activity under free-living conditions: a systematic review.

PubMed

Jeran, S; Steinbrecher, A; Pischon, T

2016-08-01

Activity-related energy expenditure (AEE) might be an important factor in the etiology of chronic diseases. However, measurement of free-living AEE is usually not feasible in large-scale epidemiological studies but instead has traditionally been estimated based on self-reported physical activity. Recently, accelerometry has been proposed for objective assessment of physical activity, but it is unclear to what extent this methods explains the variance in AEE. We conducted a systematic review searching MEDLINE database (until 2014) on studies that estimated AEE based on accelerometry-assessed physical activity in adults under free-living conditions (using doubly labeled water method). Extracted study characteristics were sample size, accelerometer (type (uniaxial, triaxial), metrics (for example, activity counts, steps, acceleration), recording period, body position, wear time), explained variance of AEE (R(2)) and number of additional predictors. The relation of univariate and multivariate R(2) with study characteristics was analyzed using nonparametric tests. Nineteen articles were identified. Examination of various accelerometers or subpopulations in one article was treated separately, resulting in 28 studies. Sample sizes ranged from 10 to 149. In most studies the accelerometer was triaxial, worn at the trunk, during waking hours and reported activity counts as output metric. Recording periods ranged from 5 to 15 days. The variance of AEE explained by accelerometer-assessed physical activity ranged from 4 to 80% (median crude R(2)=26%). Sample size was inversely related to the explained variance. Inclusion of 1 to 3 other predictors in addition to accelerometer output significantly increased the explained variance to a range of 12.5-86% (median total R(2)=41%). The increase did not depend on the number of added predictors. We conclude that there is large heterogeneity across studies in the explained variance of AEE when estimated based on accelerometry. Thus, data on predicted AEE based on accelerometry-assessed physical activity need to be interpreted cautiously.

A Formula to Calculate Standard Liver Volume Using Thoracoabdominal Circumference.

PubMed

Shaw, Brian I; Burdine, Lyle J; Braun, Hillary J; Ascher, Nancy L; Roberts, John P

2017-12-01

With the use of split liver grafts as well as living donor liver transplantation (LDLT) it is imperative to know the minimum graft volume to avoid complications. Most current formulas to predict standard liver volume (SLV) rely on weight-based measures that are likely inaccurate in the setting of cirrhosis. Therefore, we sought to create a formula for estimating SLV without weight-based covariates. LDLT donors underwent computed tomography scan volumetric evaluation of their livers. An optimal formula for calculating SLV using the anthropomorphic measure thoracoabdominal circumference (TAC) was determined using leave-one-out cross-validation. The ability of this formula to correctly predict liver volume was checked against other existing formulas by analysis of variance. The ability of the formula to predict small grafts in LDLT was evaluated by exact logistic regression. The optimal formula using TAC was determined to be SLV = (TAC × 3.5816) - (Age × 3.9844) - (Sex × 109.7386) - 934.5949. When compared to historic formulas, the current formula was the only one which was not significantly different than computed tomography determined liver volumes when compared by analysis of variance with Dunnett posttest. When evaluating the ability of the formula to predict small for size syndrome, many (10/16) of the formulas tested had significant results by exact logistic regression, with our formula predicting small for size syndrome with an odds ratio of 7.94 (95% confidence interval, 1.23-91.36; P = 0.025). We report a formula for calculating SLV that does not rely on weight-based variables that has good ability to predict SLV and identify patients with potentially small grafts.

Genetic Variance Partitioning and Genome-Wide Prediction with Allele Dosage Information in Autotetraploid Potato.

PubMed

Endelman, Jeffrey B; Carley, Cari A Schmitz; Bethke, Paul C; Coombs, Joseph J; Clough, Mark E; da Silva, Washington L; De Jong, Walter S; Douches, David S; Frederick, Curtis M; Haynes, Kathleen G; Holm, David G; Miller, J Creighton; Muñoz, Patricio R; Navarro, Felix M; Novy, Richard G; Palta, Jiwan P; Porter, Gregory A; Rak, Kyle T; Sathuvalli, Vidyasagar R; Thompson, Asunta L; Yencho, G Craig

2018-05-01

As one of the world's most important food crops, the potato ( Solanum tuberosum L.) has spurred innovation in autotetraploid genetics, including in the use of SNP arrays to determine allele dosage at thousands of markers. By combining genotype and pedigree information with phenotype data for economically important traits, the objectives of this study were to (1) partition the genetic variance into additive vs. nonadditive components, and (2) determine the accuracy of genome-wide prediction. Between 2012 and 2017, a training population of 571 clones was evaluated for total yield, specific gravity, and chip fry color. Genomic covariance matrices for additive ( G ), digenic dominant ( D ), and additive × additive epistatic ( G # G ) effects were calculated using 3895 markers, and the numerator relationship matrix ( A ) was calculated from a 13-generation pedigree. Based on model fit and prediction accuracy, mixed model analysis with G was superior to A for yield and fry color but not specific gravity. The amount of additive genetic variance captured by markers was 20% of the total genetic variance for specific gravity, compared to 45% for yield and fry color. Within the training population, including nonadditive effects improved accuracy and/or bias for all three traits when predicting total genotypic value. When six F 1 populations were used for validation, prediction accuracy ranged from 0.06 to 0.63 and was consistently lower (0.13 on average) without allele dosage information. We conclude that genome-wide prediction is feasible in potato and that it will improve selection for breeding value given the substantial amount of nonadditive genetic variance in elite germplasm. Copyright © 2018 by the Genetics Society of America.

A relative weights comparison of trauma-related shame and guilt as predictors of DSM-5 posttraumatic stress disorder symptom severity among US veterans and military members.

PubMed

Cunningham, Katherine C; Davis, Joanne L; Wilson, Sarah M; Resick, Patricia A

2018-06-01

Veterans and military service members have increased risk for post-traumatic stress disorder (PTSD) and consequent problems with health, psychosocial functioning, and quality of life. In this population and others, shame and guilt have emerged as contributors to PTSD, but there is a considerable need for research that precisely demonstrates how shame and guilt are associated with PTSD. This study examined whether a) trauma-related shame predicts PTSD severity beyond the effects of trauma-related guilt and b) shame accounts for a greater proportion of variance in PTSD symptoms than guilt. We collected cross-sectional self-report data on measures of PTSD symptom severity based on Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria, trauma-related shame, and trauma-related guilt via online survey. Participants included 61 US veterans and active duty service members. Hierarchical multiple regression and relative weights analysis were used to test hypotheses. In step 1 of regression analysis, guilt was significantly associated with PTSD. However, when shame was added to the model, the effect of guilt became non-significant, and only shame significant predicted PTSD. Results from relative weights analysis indicated that both shame and guilt predicted PTSD, jointly accounting for 46% of the variance in PTSD. Compared to guilt, trauma-related shame accounted for significantly more explained variance in PTSD. This study provided evidence that among US veterans and service members, trauma-related shame and guilt differ in their association with PTSD and that trauma-related shame, in particular, is associated with the severity of PTSD. Trauma-related shame and guilt explained almost half of the observed variance in PTSD symptom severity among this sample of US military veterans and service members. Trauma-related shame and guilt each made a unique contribution to PTSD severity after accounting for the similarity between these two emotions; however, shame was particularly associated with increased PTSD severity. These results highlight the importance of assessing and addressing trauma-related shame and guilt in PTSD treatment among military populations. We suggest that emotion- and compassion-focused techniques may be particularly relevant for addressing trauma-related shame and guilt. Limitations of the study Cross-sectional data does not allow for determination of causal relationships. Although sufficiently powered, the sample size is small. The present sample self-selected to participate in a study about stress and emotions. © 2017 The British Psychological Society.

Feasibility of histogram analysis of susceptibility-weighted MRI for staging of liver fibrosis

PubMed Central

Yang, Zhao-Xia; Liang, He-Yue; Hu, Xin-Xing; Huang, Ya-Qin; Ding, Ying; Yang, Shan; Zeng, Meng-Su; Rao, Sheng-Xiang

2016-01-01

PURPOSE We aimed to evaluate whether histogram analysis of susceptibility-weighted imaging (SWI) could quantify liver fibrosis grade in patients with chronic liver disease (CLD). METHODS Fifty-three patients with CLD who underwent multi-echo SWI (TEs of 2.5, 5, and 10 ms) were included. Histogram analysis of SWI images were performed and mean, variance, skewness, kurtosis, and the 1st, 10th, 50th, 90th, and 99th percentiles were derived. Quantitative histogram parameters were compared. For significant parameters, further receiver operating characteristic (ROC) analyses were performed to evaluate the potential diagnostic performance for differentiating liver fibrosis stages. RESULTS The number of patients in each pathologic fibrosis grade was 7, 3, 5, 5, and 33 for F0, F1, F2, F3, and F4, respectively. The results of variance (TE: 10 ms), 90th percentile (TE: 10 ms), and 99th percentile (TE: 10 and 5 ms) in F0–F3 group were significantly lower than in F4 group, with areas under the ROC curves (AUCs) of 0.84 for variance and 0.70–0.73 for the 90th and 99th percentiles, respectively. The results of variance (TE: 10 and 5 ms), 99th percentile (TE: 10 ms), and skewness (TE: 2.5 and 5 ms) in F0–F2 group were smaller than those of F3/F4 group, with AUCs of 0.88 and 0.69 for variance (TE: 10 and 5 ms, respectively), 0.68 for 99th percentile (TE: 10 ms), and 0.73 and 0.68 for skewness (TE: 2.5 and 5 ms, respectively). CONCLUSION Magnetic resonance histogram analysis of SWI, particularly the variance, is promising for predicting advanced liver fibrosis and cirrhosis. PMID:27113421

The role of early fine and gross motor development on later motor and cognitive ability.

PubMed

Piek, Jan P; Dawson, Lisa; Smith, Leigh M; Gasson, Natalie

2008-10-01

The aim of this study was to determine whether information obtained from measures of motor performance taken from birth to 4 years of age predicted motor and cognitive performance of children once they reached school age. Participants included 33 children aged from 6 years to 11 years and 6 months who had been assessed at ages 4 months to 4 years using the ages and stages questionnaires (ASQ: [Squires, J. K., Potter, L., & Bricker, D. (1995). The ages and stages questionnaire users guide. Baltimore: Brookes]). These scores were used to obtain trajectory information consisting of the age of asymptote, maximum or minimum score, and the variance of ASQ scores. At school age, both motor and cognitive ability were assessed using the McCarron Assessment of Neuromuscular Development (MAND: [McCarron, L. (1997). McCarron assessment of neuromuscular development: Fine and gross motor abilities (revised ed.). Dallas, TX: Common Market Press.]), and the Wechsler Intelligence Scale for Children-Version IV (WISC-IV: [Wechsler, D. (2004). WISC-IV integrated technical and interpretive manual. San Antonio, Texas: Harcourt Assessment]). In contrast to previous research, results demonstrated that, although socio-economic status (SES) predicted fine motor performance and three of four cognitive domains at school age, gestational age was not a significant predictor of later development. This may have been due to the low-risk nature of the sample. After controlling for SES, fine motor trajectory information did not account for a significant proportion of the variance in school aged fine motor performance or cognitive performance. The ASQ gross motor trajectory set of predictors accounted for a significant proportion of the variance for cognitive performance once SES was controlled for. Further analysis showed a significant predictive relationship for gross motor trajectory information and the subtests of working memory and processing speed. These results provide evidence for detecting children at risk of developmental delays or disorders with a parent report questionnaire prior to school age. The findings also add to recent investigations into the relationship between early motor development and later cognitive function, and support the need for ongoing research into a potential etiological relationship.

Does anxiety sensitivity predict symptoms of panic, depression, and social anxiety?

PubMed

Grant, DeMond M; Beck, J Gayle; Davila, Joanne

2007-09-01

This study examined whether the lower-order factors of the Anxiety Sensitivity Index (ASI) exhibited specificity in predicting symptoms of panic, depression, and social anxiety prospectively. This question was addressed using a sample of undergraduates stratified to represent low, medium, and high levels of anxiety sensitivity (AS). It was hypothesized that the physical concerns, mental concerns, and social concerns subscales of the ASI would predict increases in panic, depression, and social anxiety symptoms, respectively, one year later. Results found that the physical concerns subscale predicted increases in both panic and depressive symptoms. Neither the mental concerns nor the social concerns subscales predicted significant variance in any of the Time 2 symptoms. Theoretical implications of these data for AS are discussed.

Aquatic community structure in Mediterranean edge-of-field waterbodies as explained by environmental factors and the presence of pesticide mixtures.

PubMed

Pereira, Ana Santos; Dâmaso-Rodrigues, Maria Luísa; Amorim, Ana; Daam, Michiel A; Cerejeira, Maria José

2018-06-16

Studies addressing the predicted effects of pesticides in combination with abiotic and biotic factors on aquatic biota in ditches associated with typical Mediterranean agroecosystems are scarce. The current study aimed to evaluate the predicted effects of pesticides along with environmental factors and biota interactions on macroinvertebrate, zooplankton and phytoplankton community compositions in ditches adjacent to Portuguese maize and tomato crop areas. Data was analysed with the variance partitioning procedure based on redundancy analysis (RDA). The total variance in biological community composition was divided into the variance explained by the multi-substance potentially affected fraction [(msPAF) arthropods and primary producers], environmental factors (water chemistry parameters), biotic interactions, shared variance, and unexplained variance. The total explained variance reached 39.4% and the largest proportion of this explained variance was attributed to msPAF (23.7%). When each group (phytoplankton, zooplankton and macroinvertebrates) was analysed separately, biota interactions and environmental factors explained the largest proportion of variance. Results of this study indicate that besides the presence of pesticide mixtures, environmental factors and biotic interactions also considerably influence field freshwater communities. Subsequently, to increase our understanding of the risk of pesticide mixtures on ecosystem communities in edge-of-field water bodies, variations in environmental and biological factors should also be considered.

Quality of Education Predicts Performance on the Wide Range Achievement Test-4th Edition Word Reading Subtest

PubMed Central

Sayegh, Philip; Arentoft, Alyssa; Thaler, Nicholas S.; Dean, Andy C.; Thames, April D.

2014-01-01

The current study examined whether self-rated education quality predicts Wide Range Achievement Test-4th Edition (WRAT-4) Word Reading subtest and neurocognitive performance, and aimed to establish this subtest's construct validity as an educational quality measure. In a community-based adult sample (N = 106), we tested whether education quality both increased the prediction of Word Reading scores beyond demographic variables and predicted global neurocognitive functioning after adjusting for WRAT-4. As expected, race/ethnicity and education predicted WRAT-4 reading performance. Hierarchical regression revealed that when including education quality, the amount of WRAT-4's explained variance increased significantly, with race/ethnicity and both education quality and years as significant predictors. Finally, WRAT-4 scores, but not education quality, predicted neurocognitive performance. Results support WRAT-4 Word Reading as a valid proxy measure for education quality and a key predictor of neurocognitive performance. Future research should examine these findings in larger, more diverse samples to determine their robust nature. PMID:25404004

Predicting Risk Sensitivity in Humans and Lower Animals: Risk as Variance or Coefficient of Variation

ERIC Educational Resources Information Center

Weber, Elke U.; Shafir, Sharoni; Blais, Ann-Renee

2004-01-01

This article examines the statistical determinants of risk preference. In a meta-analysis of animal risk preference (foraging birds and insects), the coefficient of variation (CV), a measure of risk per unit of return, predicts choices far better than outcome variance, the risk measure of normative models. In a meta-analysis of human risk…

Do MCAT scores predict USMLE scores? An analysis on 5 years of medical student data.

PubMed

Gauer, Jacqueline L; Wolff, Josephine M; Jackson, J Brooks

2016-01-01

The purpose of this study was to determine the associations and predictive values of Medical College Admission Test (MCAT) component and composite scores prior to 2015 with U.S. Medical Licensure Exam (USMLE) Step 1 and Step 2 Clinical Knowledge (CK) scores, with a focus on whether students scoring low on the MCAT were particularly likely to continue to score low on the USMLE exams. Multiple linear regression, correlation, and chi-square analyses were performed to determine the relationship between MCAT component and composite scores and USMLE Step 1 and Step 2 CK scores from five graduating classes (2011-2015) at the University of Minnesota Medical School ( N =1,065). The multiple linear regression analyses were both significant ( p <0.001). The three MCAT component scores together explained 17.7% of the variance in Step 1 scores ( p< 0.001) and 12.0% of the variance in Step 2 CK scores ( p <0.001). In the chi-square analyses, significant, albeit weak associations were observed between almost all MCAT component scores and USMLE scores (Cramer's V ranged from 0.05 to 0.24). Each of the MCAT component scores was significantly associated with USMLE Step 1 and Step 2 CK scores, although the effect size was small. Being in the top or bottom scoring range of the MCAT exam was predictive of being in the top or bottom scoring range of the USMLE exams, although the strengths of the associations were weak to moderate. These results indicate that MCAT scores are predictive of student performance on the USMLE exams, but, given the small effect sizes, should be considered as part of the holistic view of the student.

Do MCAT scores predict USMLE scores? An analysis on 5 years of medical student data

PubMed Central

Gauer, Jacqueline L.; Wolff, Josephine M.; Jackson, J. Brooks

2016-01-01

Introduction The purpose of this study was to determine the associations and predictive values of Medical College Admission Test (MCAT) component and composite scores prior to 2015 with U.S. Medical Licensure Exam (USMLE) Step 1 and Step 2 Clinical Knowledge (CK) scores, with a focus on whether students scoring low on the MCAT were particularly likely to continue to score low on the USMLE exams. Method Multiple linear regression, correlation, and chi-square analyses were performed to determine the relationship between MCAT component and composite scores and USMLE Step 1 and Step 2 CK scores from five graduating classes (2011–2015) at the University of Minnesota Medical School (N=1,065). Results The multiple linear regression analyses were both significant (p<0.001). The three MCAT component scores together explained 17.7% of the variance in Step 1 scores (p<0.001) and 12.0% of the variance in Step 2 CK scores (p<0.001). In the chi-square analyses, significant, albeit weak associations were observed between almost all MCAT component scores and USMLE scores (Cramer's V ranged from 0.05 to 0.24). Discussion Each of the MCAT component scores was significantly associated with USMLE Step 1 and Step 2 CK scores, although the effect size was small. Being in the top or bottom scoring range of the MCAT exam was predictive of being in the top or bottom scoring range of the USMLE exams, although the strengths of the associations were weak to moderate. These results indicate that MCAT scores are predictive of student performance on the USMLE exams, but, given the small effect sizes, should be considered as part of the holistic view of the student. PMID:27702431

The Influence of Oropalatal Dimensions on the Measurement of Tongue Strength.

PubMed

Pitts, Laura L; Stierwalt, Julie A G; Hageman, Carlin F; LaPointe, Leonard L

2017-12-01

Tongue strength is routinely evaluated in clinical swallowing evaluations since lingual weakness is an established contributor to dysphagia. Tongue strength may be clinically quantified by the maximum isometric tongue pressure (MIP) generated by the tongue against the palate; however, wide ranges in normal performance remain to be fully explained. Although orthodontic theory has long suggested a relation between lingual function and oral cavity dimensions, little attention has been given to the potential influence of oral and palatal structure(s) on healthy variance in MIP generation. Therefore, anterior and posterior tongue strength measures and oropalatal dimensions were obtained across 147 healthy adults (aged 18-88 years). Age was confirmed as a significant, independent predictor explaining approximately 10.2% of the variance in anterior tongue strength, but not a significant predictor of posterior tongue strength. However, oropalatal dimensions predicted anterior tongue strength with over three times the predictive power of age alone (p < .001). Significant models for anterior tongue strength (R 2  = .457) and posterior tongue strength (R 2  = .283) included a combination of demographic predictors (i.e., age and/or gender) and oropalatal dimensions. Palatal width, estimated tongue volume, and gender were significant predictors of posterior tongue strength (p < .001). Therefore, oropalatal dimensions may warrant consideration when accurately differentiating between pathological lingual weakness and healthy individual difference.

Inheritance of Resistance to Sorghum Shoot Fly, Atherigona soccata in Sorghum, Sorghum bicolor (L.) Moench

PubMed Central

Mohammed, Riyazaddin; Are, Ashok Kumar; Munghate, Rajendra Sudhakar; Bhavanasi, Ramaiah; Polavarapu, Kavi Kishor B.; Sharma, Hari Chand

2016-01-01

Sorghum production is affected by a wide array of biotic constraints, of which sorghum shoot fly, Atherigona soccata is the most important pest, which severely damages the sorghum crop during the seedling stage. Host plant resistance is one of the major components to control sorghum shoot fly, A. soccata. To understand the nature of gene action for inheritance of shoot fly resistance, we evaluated 10 parents, 45 F1's and their reciprocals in replicated trials during the rainy and postrainy seasons. The genotypes ICSV 700, Phule Anuradha, ICSV 25019, PS 35805, IS 2123, IS 2146, and IS 18551 exhibited resistance to shoot fly damage across seasons. Crosses between susceptible parents were preferred for egg laying by the shoot fly females, resulting in a susceptible reaction. ICSV 700, ICSV 25019, PS 35805, IS 2123, IS 2146, and IS 18551 exhibited significant and negative general combining ability (gca) effects for oviposition, deadheart incidence, and overall resistance score. The plant morphological traits associated with expression of resistance/susceptibility to shoot fly damage such as leaf glossiness, plant vigor, and leafsheath pigmentation also showed significant gca effects by these genotypes, suggesting the potential for use as a selection criterion to breed for resistance to shoot fly, A. soccata. ICSV 700, Phule Anuradha, IS 2146 and IS 18551 with significant positive gca effects for trichome density can also be utilized in improving sorghums for shoot fly resistance. The parents involved in hybrids with negative specific combining ability (sca) effects for shoot fly resistance traits can be used in developing sorghum hybrids with adaptation to postrainy season. The significant reciprocal effects of combining abilities for oviposition, leaf glossy score and trichome density suggested the influence of cytoplasmic factors in inheritance of shoot fly resistance. Higher values of variance due to specific combining ability (σ2s), dominance variance (σ2d), and lower predictability ratios than the variance due to general combining ability (σ2g) and additive variance (σ2a) for shoot fly resistance traits indicated the predominance of dominance type of gene action, whereas trichome density, leaf glossy score, and plant vigor score with high σ2g, additive variance, predictability ratio, and the ratio of general combining ability to the specific combining ability showed predominance of additive type of gene action indicating importance of heterosis breeding followed by simple selection in breeding shoot fly-resistant sorghums. Most of the traits exhibited high broadsense heritability, indicating high inheritance of shoot fly resistance traits. PMID:27200020

Longitudinal Change in the Relationship between Fundamental Motor Skills and Perceived Competence: Kindergarten to Grade 2

PubMed Central

Naylor, Patti-Jean

2017-01-01

As children transition from early to middle childhood, the relationship between motor skill proficiency and perceptions of physical competence should strengthen as skills improve and inflated early childhood perceptions decrease. This study examined change in motor skills and perceptions of physical competence and the relationship between those variables from kindergarten to grade 2. Participants were 250 boys and girls (Mean age = 5 years 8 months in kindergarten). Motor skills were assessed using the Test of Gross Motor Development-2 and perceptions were assessed using a pictorial scale of perceived competence. Mixed-design analyses of variance revealed there was a significant increase in object-control skills and perceptions from kindergarten to grade 2, but no change in locomotor skills. In kindergarten, linear regression showed that locomotor skills and object-control skills explained 10% and 9% of the variance, respectively, in perceived competence for girls, and 7% and 11%, respectively, for boys. In grade 2, locomotor skills predicted 11% and object-control skills predicted 19% of the variance in perceptions of physical competence, but only among the boys. Furthermore, the relationship between motor skills and perceptions of physical competence strengthened for boys only from early to middle childhood. However, it seems that forces other than motor skill proficiency influenced girls’ perceptions of their abilities in grade 2.

Within-patient temporal variance in MELD score and impact on survival prediction after TIPS creation.

PubMed

Gaba, Ron C; Shah, Kruti D; Couture, Patrick M; Parvinian, Ahmad; Minocha, Jeet; Knuttinen, M Grace; Bui, James T

2013-01-01

To assess within-patient temporal variability in Model for End Stage Liver Disease (MELD) scores and impact on outcome prognostication after transjugular intrahepatic portosystemic shunt (TIPS) creation. In this single institution retrospective study, MELD score was calculated in 68 patients (M:F = 42:26, mean age 55 years) at 4 pre-procedure time points (1, 2-6, 7-14, and 15-35 days) before TIPS creation. Medical record review was used to identify 30- and 90-day clinical outcomes. Within-patient variability in pre-procedure MELD scores was assessed using repeated measures analysis of variance, and the ability of MELD scores at different time points to predict post-TIPS mortality was evaluated by comparing area under receiver operating characteristic (AUROC) curves. TIPS were successfully created for ascites (n = 30), variceal hemorrhage (n = 29), hepatic hydrothorax (n = 8), and portal vein thrombosis (n = 1). Pre-TIPS MELD scores showed significant (P = 0.032) within-subject variance that approached ± 18.5%. Higher MELD scores demonstrated greater variability in sequential scores as compared to lower MELD scores. Overall 30- and 90-day patient mortality was 22% (15/67) and 38% (24/64). AUROC curves showed that most recent MELD scores performed on the day of TIPS had superior predictive capacity for 30- (0.876, P = 0.037) and 90-day (0.805 P = 0.020) mortality compared to MELD scores performed 2-6 or 7-14 days prior. In conclusion, MELD scores show within-patient variability over time, and scores calculated on the day of TIPS most accurately predict risk and should be used for patient selection and counseling.

Acculturation Stress and Drinking Problems Among Urban Heavy Drinking Latinos in the Northeast

PubMed Central

Lee, Christina S.; Colby, Suzanne M.; Rohsenow, Damaris J.; López, Steven R.; Hernández, Lynn; Caetano, Raul

2014-01-01

This study investigates the relationship between level of acculturation and acculturation stress, and the extent to which each predicts problems related to drinking. Hispanics who met criteria for hazardous drinking completed measures of acculturation, acculturation stress, and drinking problems. Sequential multiple regression was used to determine whether levels of self-reported acculturation stress predicted concurrent alcohol problems after controlling for the predictive value of acculturation level. Acculturation stress accounted for significant variance in drinking problems while adjusting for acculturation, income, and education. Choosing to drink in response to acculturation stress should be an intervention target with Hispanic heavy drinkers. PMID:24215224

Acculturation stress and drinking problems among urban heavy drinking Latinos in the Northeast.

PubMed

Lee, Christina S; Colby, Suzanne M; Rohsenow, Damaris J; López, Steven R; Hernández, Lynn; Caetano, Raul

2013-01-01

This study investigates the relationship between the level of acculturation and acculturation stress and the extent to which each predicts problems related to drinking. Hispanics who met criteria for hazardous drinking completed measures of acculturation, acculturation stress, and drinking problems. Sequential multiple regression was used to determine whether the levels of self-reported acculturation stress predicted concurrent alcohol problems after controlling for the predictive value of the acculturation level. Acculturation stress accounted for a significant variance in drinking problems, while adjusting for acculturation, income, and education. Choosing to drink in response to acculturation stress should be an intervention target with Hispanic heavy drinkers.

Predicting healthy eating intention and adherence to dietary recommendations during pregnancy in Australia using the Theory of Planned Behaviour.

PubMed

Malek, Lenka; Umberger, Wendy J; Makrides, Maria; ShaoJia, Zhou

2017-09-01

This study aims to aid in the development of more effective healthy eating intervention strategies for pregnant women by understanding the relationship between healthy eating intention and actual eating behaviour. Specifically, the study explored whether Theory of Planned Behaviour (TPB) constructs [attitude, subjective-norm, perceived-behavioural-control (PBC)] and additional psychosocial variables (perceived stress, health value and self-identity as a healthy eater) are useful in explaining variance in women's 1) intentions to consume a healthy diet during pregnancy and 2) food consumption behaviour (e.g. adherence to food group recommendations) during pregnancy. A cross-sectional sample of 455 Australian pregnant women completed a TPB questionnaire as part of a larger comprehensive web-based nutrition questionnaire. Women's perceived stress, health value and self-identity as a healthy eater were also measured. Dietary intake was assessed using six-items based on the 2013 Australian Dietary Guidelines. Hierarchical multiple linear regression models were estimated (significance level <0.05), which explained 70% of the variance in healthy eating intention scores and 12% of the variance in adherence to food group recommendations. TPB constructs explained 66% of the total variance in healthy eating intention. Significant predictors of stronger healthy eating intention were greater PBC and subjective norm, followed by positive attitude and stronger self-identity as a healthy eater. Conversely, TPB constructs collectively explained only 3.4% of total variance in adherence to food group recommendations. These findings reveal that the TPB framework explains considerable variance in healthy eating intention during pregnancy, but explains little variance in actual food consumption behaviour. Further research is required to understand this weak relationship between healthy eating intention and behaviour during pregnancy. Alternative behavioural frameworks, particularly those that account for the automatic nature of most dietary choices, should also be considered. Copyright © 2017 Elsevier Ltd. All rights reserved.

Value of MR histogram analyses for prediction of microvascular invasion of hepatocellular carcinoma

PubMed Central

Huang, Ya-Qin; Liang, He-Yue; Yang, Zhao-Xia; Ding, Ying; Zeng, Meng-Su; Rao, Sheng-Xiang

2016-01-01

Abstract The objective is to explore the value of preoperative magnetic resonance (MR) histogram analyses in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Fifty-one patients with histologically confirmed HCC who underwent diffusion-weighted and contrast-enhanced MR imaging were included. Histogram analyses were performed and mean, variance, skewness, kurtosis, 1th, 10th, 50th, 90th, and 99th percentiles were derived. Quantitative histogram parameters were compared between HCCs with and without MVI. Receiver operating characteristics (ROC) analyses were generated to compare the diagnostic performance of tumor size, histogram analyses of apparent diffusion coefficient (ADC) maps, and MR enhancement. The mean, 1th, 10th, and 50th percentiles of ADC maps, and the mean, variance. 1th, 10th, 50th, 90th, and 99th percentiles of the portal venous phase (PVP) images were significantly different between the groups with and without MVI (P <0.05), with area under the ROC curves (AUCs) of 0.66 to 0.74 for ADC and 0.76 to 0.88 for PVP. The largest AUC of PVP (1th percentile) showed significantly higher accuracy compared with that of arterial phase (AP) or tumor size (P <0.001). MR histogram analyses—in particular for 1th percentile for PVP images—held promise for prediction of MVI of HCC. PMID:27368028

The effects of conscientiousness on the appraisals of daily stressors.

PubMed

Gartland, Nicola; O'Connor, Daryl B; Lawton, Rebecca

2012-02-01

Conscientiousness (C) is positively associated with health and longevity although the mechanisms underlying this relationship are not fully understood. Stress may play a role in explaining the C-longevity relationship. This study investigated whether C predicted the cognitive appraisals of daily stressors/hassles. Participants (N=102) completed measures of C and cognitive appraisal in relation to the most stressful hassle they had experienced in the last 7 days. Correlational analysis revealed that Total C, Order and Industriousness were positively correlated with primary appraisals, and Responsibility was positively correlated with secondary appraisals. The facets of C were then entered into hierarchical regression models, controlling for age and gender. This demonstrated that Order (β=0.27, p<0.05) and Industriousness (β=0.28, p<0.05) significantly predicted primary appraisals, accounting for 15.8% of the variance. Responsibility significantly predicted secondary appraisals (β=0.44, p<0.01), accounting for 16.3% of the variance. These findings indicate that higher Order and Industriousness are related to having a greater stake in daily stressors, whereas higher Responsibility is related to greater confidence in one's ability to deal with daily stressors. These results are the first demonstration that C is related to the appraisals of daily hassles and suggest that C may moderate the experience of stress in daily life. Copyright © 2011 John Wiley & Sons, Ltd.

Factors Predicting Cybersex Use and Difficulties in Forming Intimate Relationships among Male and Female Users of Cybersex

PubMed Central

Weinstein, Aviv M.; Zolek, Rinat; Babkin, Anna; Cohen, Koby; Lejoyeux, Michel

2015-01-01

Sexual addiction otherwise known as compulsive sexual behavior is associated with serious psychosocial problems and risk-taking behavior. This study used the Cybersex addiction test, Craving for pornography questionnaire, and a Questionnaire on intimacy among 267 participants (192 males and 75 females) mean age for males 28.16 (SD = 6.8) and for females 25.5 (SD = 5.13) who were recruited from special sites that are dedicated to pornography and cybersex on the Internet. Results of regression analysis indicated that pornography, gender, and cybersex significantly predicted difficulties in intimacy and it accounted for 66.1% of the variance of rating on the intimacy questionnaire. Second, regression analysis also indicated that craving for pornography, gender, and difficulties in forming intimate relationships significantly predicted frequency of cybersex use and it accounted for 83.7% of the variance in ratings of cybersex use. Third, men had higher scores of frequency of using cybersex than women [t(2,224) = 1.97, p < 0.05] and higher scores of craving for pornography than women [t(2,265) = 3.26, p < 0.01] and no higher scores on the questionnaire measuring difficulties in forming intimate relationship than women [t(2,224) = 1, p = 0.32]. These findings support previous evidence for sex differences in compulsive sexual behavior. PMID:25941496

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.

Display format, highlight validity, and highlight method: Their effects on search performance

NASA Technical Reports Server (NTRS)

Donner, Kimberly A.; Mckay, Tim D.; Obrien, Kevin M.; Rudisill, Marianne

1991-01-01

Display format and highlight validity were shown to affect visual display search performance; however, these studies were conducted on small, artificial displays of alphanumeric stimuli. A study manipulating these variables was conducted using realistic, complex Space Shuttle information displays. A 2x2x3 within-subjects analysis of variance found that search times were faster for items in reformatted displays than for current displays. Responses to valid applications of highlight were significantly faster than responses to non or invalidly highlighted applications. The significant format by highlight validity interaction showed that there was little difference in response time to both current and reformatted displays when the highlight validity was applied; however, under the non or invalid highlight conditions, search times were faster with reformatted displays. A separate within-subject analysis of variance of display format, highlight validity, and several highlight methods did not reveal a main effect of highlight method. In addition, observed display search times were compared to search time predicted by Tullis' Display Analysis Program. Benefits of highlighting and reformatting displays to enhance search and the necessity to consider highlight validity and format characteristics in tandem for predicting search performance are discussed.

Dysthymic disorder contributes to oppositional defiant behaviour in children with Attention Deficit Hyperactivity Disorder, combined type (ADHD-CT).

PubMed

Vance, Alasdair; Sanders, Michelle; Arduca, Yolanda

2005-06-01

The specific relationships between oppositional defiant disorder (ODD), ADHD-CT, dysthymic disorder (DD) and anxiety disorders symptoms have not been studied in children with ADHD-CT. The relationship to DD is important because DD is common, has an earlier age of onset, is associated with significant morbidity and with increased rates of treatment non-responsiveness when comorbid with major depressive disorder and/or ADHD-CT. 200 clinically referred children with ADHD-CT, without comorbid major depressive disorder, were identified. "ODD", "ADHD-CT", "DD" and "anxiety disorders" symptoms were defined by composite measures of (1) semi-structured clinical interview and (2) parent and/or child standardized questionnaires. Standard multiple regression was used to examine how well "ADHD-CT", "DD" and "anxiety disorders" symptoms predict "ODD" symptoms. Only "ADHD-CT" (15% of the variance) and "DD" (8% of the variance) symptoms made independent significant contributions to the prediction of "ODD" symptoms. The study's sample size did not allow "ODD" and "conduct disorder" symptoms to be analysed separately. The association of DD with ODD may reflect a unique contribution of DD to ODD in children, whether ADHD-CT is present or not, or only when ADHD-CT is present.

Personal and environmental characteristics predicting burnout among certified athletic trainers at National Collegiate Athletic Association institutions.

PubMed

Kania, Michelle L; Meyer, Barbara B; Ebersole, Kyle T

2009-01-01

Recent research in the health care professions has shown that specific personal and environmental characteristics can predict burnout, which is a negative coping strategy related to stressful situations. Burnout has been shown to result in physiologic (eg, headaches, difficulty sleeping, poor appetite), psychological (eg, increased negative self-talk, depression, difficulty in interpersonal relationships), and behavioral (eg, diminished care, increased absenteeism, attrition) symptoms. To examine the relationship between selected personal and environmental characteristics and burnout among certified athletic trainers (ATs). Cross-sectional survey. A demographic survey that was designed for this study and the Maslach Burnout Inventory-Human Services Survey. A total of 206 ATs employed at National Collegiate Athletic Association (NCAA) institutions as clinical ATs volunteered. We assessed personal and environmental characteristics of ATs with the demographic survey and measured burnout using the Maslach Burnout Inventory-Human Services Survey. Multiple regression analyses were performed to examine relationships between specific personal and environmental characteristics and each of the 3 subscales of burnout (emotional exhaustion, depersonalization, personal accomplishment). Most ATs we surveyed experienced low to average levels of burnout. Personal characteristics predicted 45.5% of the variance in emotional exhaustion (P < .001), 21.5% of the variance in depersonalization (P < .001), and 24.8% of the variance in personal accomplishment (P < .001). Environmental characteristics predicted 16.7% of the variance in emotional exhaustion (P = .005), 14.4% of the variance in depersonalization (P = .024), and 10.4% of the variance in personal accomplishment (P = .209). Stress level and coaches' pressure to medically clear athletes predicted ratings on all 3 subscales of burnout. Our findings were similar to those of other studies of burnout among NCAA Division I ATs, coaches, and coach-teachers. The results also support the Cognitive-Affective Model of Athletic Burnout proposed by Smith. Finally, these results indicate new areas of concentration for burnout research and professional practice.

General object recognition is specific: Evidence from novel and familiar objects.

PubMed

Richler, Jennifer J; Wilmer, Jeremy B; Gauthier, Isabel

2017-09-01

In tests of object recognition, individual differences typically correlate modestly but nontrivially across familiar categories (e.g. cars, faces, shoes, birds, mushrooms). In theory, these correlations could reflect either global, non-specific mechanisms, such as general intelligence (IQ), or more specific mechanisms. Here, we introduce two separate methods for effectively capturing category-general performance variation, one that uses novel objects and one that uses familiar objects. In each case, we show that category-general performance variance is unrelated to IQ, thereby implicating more specific mechanisms. The first approach examines three newly developed novel object memory tests (NOMTs). We predicted that NOMTs would exhibit more shared, category-general variance than familiar object memory tests (FOMTs) because novel objects, unlike familiar objects, lack category-specific environmental influences (e.g. exposure to car magazines or botany classes). This prediction held, and remarkably, virtually none of the substantial shared variance among NOMTs was explained by IQ. Also, while NOMTs correlated nontrivially with two FOMTs (faces, cars), these correlations were smaller than among NOMTs and no larger than between the face and car tests themselves, suggesting that the category-general variance captured by NOMTs is specific not only relative to IQ, but also, to some degree, relative to both face and car recognition. The second approach averaged performance across multiple FOMTs, which we predicted would increase category-general variance by averaging out category-specific factors. This prediction held, and as with NOMTs, virtually none of the shared variance among FOMTs was explained by IQ. Overall, these results support the existence of object recognition mechanisms that, though category-general, are specific relative to IQ and substantially separable from face and car recognition. They also add sensitive, well-normed NOMTs to the tools available to study object recognition. Copyright © 2017 Elsevier B.V. All rights reserved.

Sex-dependent expression of behavioural genetic architectures and the evolution of sexual dimorphism.

PubMed

Han, Chang S; Dingemanse, Niels J

2017-10-11

Empirical studies imply that sex-specific genetic architectures can resolve evolutionary conflicts between males and females, and thereby facilitate the evolution of sexual dimorphism. Sex-specificity of behavioural genetic architectures has, however, rarely been considered. Moreover, as the expression of genetic (co)variances is often environment-dependent, general inferences on sex-specific genetic architectures require estimates of quantitative genetics parameters under multiple conditions. We measured exploration and aggression in pedigreed populations of southern field crickets ( Gryllus bimaculatus ) raised on either naturally balanced (free-choice) or imbalanced (protein-deprived) diets. For each dietary condition, we measured for each behavioural trait (i) level of sexual dimorphism, (ii) level of sex-specificity of survival selection gradients, (iii) level of sex-specificity of additive genetic variance, and (iv) strength of the cross-sex genetic correlation. We report here evidence for sexual dimorphism in behaviour as well as sex-specificity in the expression of genetic (co)variances as predicted by theory. The additive genetic variances of exploration and aggression were significantly greater in males compared with females. Cross-sex genetic correlations were highly positive for exploration but deviating (significantly) from one for aggression; findings were consistent across dietary treatments. This suggests that genetic architectures characterize the sexually dimorphic focal behaviours across various key environmental conditions in the wild. Our finding also highlights that sexual conflict can be resolved by evolving sexually independent genetic architectures. © 2017 The Author(s).

Comparison of Turbulent Thermal Diffusivity and Scalar Variance Models

NASA Technical Reports Server (NTRS)

Yoder, Dennis A.

2016-01-01

In this study, several variable turbulent Prandtl number formulations are examined for boundary layers, pipe flow, and axisymmetric jets. The model formulations include simple algebraic relations between the thermal diffusivity and turbulent viscosity as well as more complex models that solve transport equations for the thermal variance and its dissipation rate. Results are compared with available data for wall heat transfer and profile measurements of mean temperature, the root-mean-square (RMS) fluctuating temperature, turbulent heat flux and turbulent Prandtl number. For wall-bounded problems, the algebraic models are found to best predict the rise in turbulent Prandtl number near the wall as well as the log-layer temperature profile, while the thermal variance models provide a good representation of the RMS temperature fluctuations. In jet flows, the algebraic models provide no benefit over a constant turbulent Prandtl number approach. Application of the thermal variance models finds that some significantly overpredict the temperature variance in the plume and most underpredict the thermal growth rate of the jet. The models yield very similar fluctuating temperature intensities in jets from straight pipes and smooth contraction nozzles, in contrast to data that indicate the latter should have noticeably higher values. For the particular low subsonic heated jet cases examined, changes in the turbulent Prandtl number had no effect on the centerline velocity decay.

Research on Improved Depth Belief Network-Based Prediction of Cardiovascular Diseases

PubMed Central

Zhang, Hongpo

2018-01-01

Quantitative analysis and prediction can help to reduce the risk of cardiovascular disease. Quantitative prediction based on traditional model has low accuracy. The variance of model prediction based on shallow neural network is larger. In this paper, cardiovascular disease prediction model based on improved deep belief network (DBN) is proposed. Using the reconstruction error, the network depth is determined independently, and unsupervised training and supervised optimization are combined. It ensures the accuracy of model prediction while guaranteeing stability. Thirty experiments were performed independently on the Statlog (Heart) and Heart Disease Database data sets in the UCI database. Experimental results showed that the mean of prediction accuracy was 91.26% and 89.78%, respectively. The variance of prediction accuracy was 5.78 and 4.46, respectively. PMID:29854369

Neurocognitive correlates of helplessness, hopelessness, and well-being in schizophrenia.

PubMed

Lysaker, P H; Clements, C A; Wright, D E; Evans, J; Marks, K A

2001-07-01

Persons with schizophrenia are widely recognized to experience potent feelings of hopelessness, helplessness, and a fragile sense of well-being. Although these subjective experiences have been linked to positive symptoms, little is known about their relationship to neurocognition. Accordingly, this study examined the relationship of self-reports of hope, self-efficacy, and well-being to measures of neurocognition, symptoms, and coping among 49 persons with schizophrenia or schizoaffective disorder. Results suggest that poorer executive function, verbal memory, and a greater reliance on escape avoidance as a coping mechanism predicted significantly higher levels of hope and well being with multiple regressions accounting for 34% and 20% of the variance (p < .0001), respectively. Self-efficacy predicted lower levels of positive symptoms and greater preference for escape avoidance as a coping mechanism with a multiple repression accounting for 9% of the variance (p < .05). Results may suggest that higher levels of neurocognitive impairment and an avoidant coping style may shield some with schizophrenia from painful subjective experiences. Theoretical and practical implications for rehabilitation are discussed.

Predicting clinical concussion measures at baseline based on motivation and academic profile.

PubMed

Trinidad, Katrina J; Schmidt, Julianne D; Register-Mihalik, Johna K; Groff, Diane; Goto, Shiho; Guskiewicz, Kevin M

2013-11-01

The purpose of this study was to predict baseline neurocognitive and postural control performance using a measure of motivation, high school grade point average (hsGPA), and Scholastic Aptitude Test (SAT) score. Cross-sectional. Clinical research center. Eighty-eight National Collegiate Athletic Association Division I incoming student-athletes (freshman and transfers). Participants completed baseline clinical concussion measures, including a neurocognitive test battery (CNS Vital Signs), a balance assessment [Sensory Organization Test (SOT)], and motivation testing (Rey Dot Counting). Participants granted permission to access hsGPA and SAT total score. Standard scores for each CNS Vital Signs domain and SOT composite score. Baseline motivation, hsGPA, and SAT explained a small percentage of the variance of complex attention (11%), processing speed (12%), and composite SOT score (20%). Motivation, hsGPA, and total SAT score do not explain a significant amount of the variance in neurocognitive and postural control measures but may still be valuable to consider when interpreting neurocognitive and postural control measures.

Predicting Levels of Reading and Writing Achievement in Typically Developing, English-Speaking 2nd and 5th Graders

PubMed Central

Jones, Jasmin Niedo; Abbott, Robert D.; Berninger, Virginia W.

2014-01-01

Human traits tend to fall along normal distributions. The aim of this research was to evaluate an evidence-based conceptual framework for predicting expected individual differences in reading and writing achievement outcomes for typically developing readers and writers in early and middle childhood from Verbal Reasoning with or without Working Memory Components (phonological, orthographic, and morphological word storage and processing units, phonological and orthographic loops, and rapid switching attention for cross-code integration). Verbal Reasoning (reconceptualized as Bidirectional Cognitive-Linguistic Translation) plus the Working Memory Components (reconceptualized as a language learning system) accounted for more variance than Verbal Reasoning alone, except for handwriting for which Working Memory Components alone were better predictors. Which predictors explained unique variance varied within and across reading (oral real word and pseudoword accuracy and rate, reading comprehension) and writing (handwriting, spelling, composing) skills and grade levels (second and fifth) in this longitudinal study. Educational applications are illustrated and theoretical and practical significance discussed. PMID:24948868

The Impact of Early Classroom Inattention on Phonological Processing and Word-Reading Development.

PubMed

Dittman, Cassandra K

2016-08-01

The present study investigated the longitudinal relationships between inattention, phonological processing and word reading across the first 2 years of formal reading instruction. In all, 136 school entrants were administered measures of letter knowledge, phonological awareness, phonological memory, rapid naming, and word reading at the start and end of their 1st year of school, and the end of their 2nd year, while teachers completed rating scales of inattention. School entry inattentiveness predicted unique variance in word reading at the end of first grade, after controlling for verbal ability, letter knowledge, and phonological processing. End-of-first-grade inattention predicted a small but significant amount of unique variance in second-grade word reading and word-reading efficiency. Inattention, however, was not a reliable predictor of phonological processing in either first or second grade. Early classroom inattentiveness influences learning to read independent of critical developmental precursors of word-reading development. © The Author(s) 2013.

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.

Auditory brainstem responses to stop consonants predict literacy.

PubMed

Neef, Nicole E; Schaadt, Gesa; Friederici, Angela D

2017-03-01

Precise temporal coding of speech plays a pivotal role in sound processing throughout the central auditory system, which, in turn, influences literacy acquisition. The current study tests whether an electrophysiological measure of this precision predicts literacy skills. Complex auditory brainstem responses were analysed from 62 native German-speaking children aged 11-13years. We employed the cross-phaseogram approach to compute the quality of the electrophysiological stimulus contrast [da] and [ba]. Phase shifts were expected to vary with literacy. Receiver operating curves demonstrated a feasible sensitivity and specificity of the electrophysiological measure. A multiple regression analysis resulted in a significant prediction of literacy by delta cross-phase as well as phonological awareness. A further commonality analysis separated a unique variance that was explained by the physiological measure, from a unique variance that was explained by the behavioral measure, and common effects of both. Despite multicollinearities between literacy, phonological awareness, and subcortical differentiation of stop consonants, a combined assessment of behavior and physiology strongly increases the ability to predict literacy skills. The strong link between the neurophysiological signature of sound encoding and literacy outcome suggests that the delta cross-phase could indicate the risk of dyslexia and thereby complement subjective psychometric measures for early diagnoses. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Assessing Dependency using Self-report and Indirect Measures: Examining the Significance of Discrepancies

PubMed Central

Cogswell, Alex; Alloy, Lauren B.; Karpinski, Andrew; Grant, David

2011-01-01

The present study addressed convergence between self-report and indirect approaches to assessing dependency. The study was moderately successful in validating an implicit measure, which was found to be reliable, orthogonal to two self-report instruments, and predictive of external criteria. This study also examined discrepancies between scores on self-report and implicit measures, and has implications for their significance. The possibility that discrepancies themselves are pathological was not supported, although discrepancies were associated with particular personality profiles. Finally, this study offered additional evidence for the relation between dependency and depressive symptomatology, and identified implicit dependency as contributing unique variance in predicting past major depression. PMID:20552505

Predictors of smoking cessation in Taiwan: using the theory of planned behavior.

PubMed

Tseng, Yu-Fang; Wang, Kuei-Lan; Lin, Ching-Yun; Lin, Yi-Ting; Pan, Hui-Chen; Chang, Chai-Jan

2018-03-01

This study aimed to explore the factors predicting the intention to quit smoking and the subsequent behavior 6 months later using the theory of planned behavior (TPB). Data were obtained from 145 smokers who attended a smoking cessation clinic in a community hospital. All participants completed a questionnaire which included demographic information, TPB-based items, perceived susceptibility and previous attempts to quit. The actual quitting behavior was obtained by follow-up phone calls 6 months later. The TPB constructs explained 34% of the variance in intention to quit smoking. By adding perceived susceptibility, the explained variance was significantly improved to 40%. The most important predictors were perceived behavior control and perceived susceptibility, followed by attitude. Subjective norm did not contribute to the prediction of intention. Attitude and perceived behavior control contributed to the prediction of actual quitting behavior, but intention, subjective norm and perceived susceptibility did not. Our findings support that the TPB is generally a useful framework to predict the intention to quit smoking in Taiwan. The inclusion of perceived susceptibility improved the prediction of intention. With regards to successfully quitting, attitude and perceived behavior control played more crucial roles than other TPB constructs. Smoking cessation promotion initiatives focusing on reinforcing cessation belief, enhancing a smoker's perception of their capability to quit smoking, and persuading smokers that they can overcome cessation barriers to cessation could make subsequent interventions more effective.

Deterministic theory of Monte Carlo variance

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

Ueki, T.; Larsen, E.W.

1996-12-31

The theoretical estimation of variance in Monte Carlo transport simulations, particularly those using variance reduction techniques, is a substantially unsolved problem. In this paper, the authors describe a theory that predicts the variance in a variance reduction method proposed by Dwivedi. Dwivedi`s method combines the exponential transform with angular biasing. The key element of this theory is a new modified transport problem, containing the Monte Carlo weight w as an extra independent variable, which simulates Dwivedi`s Monte Carlo scheme. The (deterministic) solution of this modified transport problem yields an expression for the variance. The authors give computational results that validatemore » this theory.« less

Direct and indirect genetic and fine-scale location effects on breeding date in song sparrows.

PubMed

Germain, Ryan R; Wolak, Matthew E; Arcese, Peter; Losdat, Sylvain; Reid, Jane M

2016-11-01

Quantifying direct and indirect genetic effects of interacting females and males on variation in jointly expressed life-history traits is central to predicting microevolutionary dynamics. However, accurately estimating sex-specific additive genetic variances in such traits remains difficult in wild populations, especially if related individuals inhabit similar fine-scale environments. Breeding date is a key life-history trait that responds to environmental phenology and mediates individual and population responses to environmental change. However, no studies have estimated female (direct) and male (indirect) additive genetic and inbreeding effects on breeding date, and estimated the cross-sex genetic correlation, while simultaneously accounting for fine-scale environmental effects of breeding locations, impeding prediction of microevolutionary dynamics. We fitted animal models to 38 years of song sparrow (Melospiza melodia) phenology and pedigree data to estimate sex-specific additive genetic variances in breeding date, and the cross-sex genetic correlation, thereby estimating the total additive genetic variance while simultaneously estimating sex-specific inbreeding depression. We further fitted three forms of spatial animal model to explicitly estimate variance in breeding date attributable to breeding location, overlap among breeding locations and spatial autocorrelation. We thereby quantified fine-scale location variances in breeding date and quantified the degree to which estimating such variances affected the estimated additive genetic variances. The non-spatial animal model estimated nonzero female and male additive genetic variances in breeding date (sex-specific heritabilities: 0·07 and 0·02, respectively) and a strong, positive cross-sex genetic correlation (0·99), creating substantial total additive genetic variance (0·18). Breeding date varied with female, but not male inbreeding coefficient, revealing direct, but not indirect, inbreeding depression. All three spatial animal models estimated small location variance in breeding date, but because relatedness and breeding location were virtually uncorrelated, modelling location variance did not alter the estimated additive genetic variances. Our results show that sex-specific additive genetic effects on breeding date can be strongly positively correlated, which would affect any predicted rates of microevolutionary change in response to sexually antagonistic or congruent selection. Further, we show that inbreeding effects on breeding date can also be sex specific and that genetic effects can exceed phenotypic variation stemming from fine-scale location-based variation within a wild population. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

Temperament and job stress in Japanese company employees.

PubMed

Sakai, Y; Akiyama, T; Miyake, Y; Kawamura, Y; Tsuda, H; Kurabayashi, L; Tominaga, M; Noda, T; Akiskal, K; Akiskal, H

2005-03-01

This study aims to demonstrate the relevance of temperament to job stress. The subjects were 848 male and 366 female Japanese company employees. Temperament Evaluation of Memphis, Pisa, Paris and San Diego-Autoquestionnaire version (TEMPS-A) and Munich Personality Test (MPT) were administered to assess temperaments, and the NIOSH Generic Job Stress Questionnaire (GJSQ) to assess job stress. We used hierarchical multiple linear regression analysis in order to demonstrate whether temperament variables added any unique variance after controlling the effects of other predictors such as gender, age and job rank. In all subscales of the GJSQ, temperament predicted a large share of the variance in job stress. Remarkably, for interpersonal relationship stressors, the temperament variables added greater variance than that predicted by gender, age and job rank. Summary of the hierarchical linear regression analysis showed that the irritable temperament was associated with the most prominent vulnerability, followed by cyclothymic and anxious temperaments. The schizoid temperament had difficulty in the area of social support. On the other hand, the hyperthymic temperament displayed significant robustness in facing most job stressors; the melancholic type showed a similar pattern to a lesser degree. The findings may be different in a clinical Japanese sample, or a cohort of healthy employees from a different cultural background. Temperament influences job stress significantly-indeed, it impacts on such stress with greater magnitude than age, gender and job rank in most areas examined. Temperament influences interpersonal relationship stressors more than workload-related stressors. Interestingly, in line with previous clinical and theoretical formulations, the hyperthymic and melancholic types actually appear to be "hyper-adapted" to the workplace.

The role of attitudes about vaccine safety, efficacy, and value in explaining parents' reported vaccination behavior.

PubMed

Lavail, Katherine Hart; Kennedy, Allison Michelle

2013-10-01

To explain vaccine confidence as it related to parents' decisions to vaccinate their children with recommended vaccines, and to develop a confidence measure to efficiently and effectively predict parents' self-reported vaccine behaviors. A sample of parents with at least one child younger than 6 years (n = 376) was analyzed using data from the HealthStyles 2010 survey. Questions were grouped into block variables to create three confidence constructs: value, safety, and efficacy. Regression equations controlling for demographic characteristics were used to identify the confidence construct(s) that best predicted parents' self-reported vaccination decisions (accept all, some, or none of the recommended childhood vaccines). Among the three constructs evaluated, confidence in the value of vaccines, that is the belief that vaccines are important and vaccinating one's children is the right thing to do, was the best predictor of parents' vaccine decisions, F(2, 351) = 119.199, p < .001. When combined into a block variable for analysis, two survey items measuring confidence in the value of vaccines accounted for 40% of the variance in parents' self-reported vaccine decisions. Confidence in the safety or efficacy of vaccines failed to account for additional significant variance in parent-reported vaccination behavior. Confidence in the value of vaccines is a helpful predictor of parent-reported vaccination behavior. Attitudinal constructs of confidence in the safety and efficacy of vaccines failed to account for additional significant variance in parents' vaccination behaviors. Future research should assess the role of vaccine knowledge and tangible barriers, such as access and cost, to further explain parents' vaccination behaviors.

Maternal factors predicting cognitive and behavioral characteristics of children with fetal alcohol spectrum disorders.

PubMed

May, Philip A; Tabachnick, Barbara G; Gossage, J Phillip; Kalberg, Wendy O; Marais, Anna-Susan; Robinson, Luther K; Manning, Melanie A; Blankenship, Jason; Buckley, David; Hoyme, H Eugene; Adnams, Colleen M

2013-06-01

To provide an analysis of multiple predictors of cognitive and behavioral traits for children with fetal alcohol spectrum disorders (FASDs). Multivariate correlation techniques were used with maternal and child data from epidemiologic studies in a community in South Africa. Data on 561 first-grade children with fetal alcohol syndrome (FAS), partial FAS (PFAS), and not FASD and their mothers were analyzed by grouping 19 maternal variables into categories (physical, demographic, childbearing, and drinking) and used in structural equation models (SEMs) to assess correlates of child intelligence (verbal and nonverbal) and behavior. A first SEM using only 7 maternal alcohol use variables to predict cognitive/behavioral traits was statistically significant (B = 3.10, p < .05) but explained only 17.3% of the variance. The second model incorporated multiple maternal variables and was statistically significant explaining 55.3% of the variance. Significantly correlated with low intelligence and problem behavior were demographic (B = 3.83, p < .05) (low maternal education, low socioeconomic status [SES], and rural residence) and maternal physical characteristics (B = 2.70, p < .05) (short stature, small head circumference, and low weight). Childbearing history and alcohol use composites were not statistically significant in the final complex model and were overpowered by SES and maternal physical traits. Although other analytic techniques have amply demonstrated the negative effects of maternal drinking on intelligence and behavior, this highly controlled analysis of multiple maternal influences reveals that maternal demographics and physical traits make a significant enabling or disabling contribution to child functioning in FASD.

Predicting Intended and Self-perceived Sugar Restriction among Tanzanian Students using the Theory of Planned Behavior.

PubMed

Masalu, J R; Astrøm, A N

2001-07-01

This study examines the applicability and sufficiency of the Theory of Planned Behavior (TPB) in predicting intention and self-perceived behavior with respect to avoiding between-meal intake of sugared snacks and drinks. One thousand one hundred and twenty-three Tanzanian students (mean age 26.4 years) completed self-administered questionnaires designed to measure the components of the TPB during May-July, 1999. Self-perceived sugar consumption was obtained in a subsample of respondents (n = 228) four weeks later. The TPB provided a significant prediction of intention (R(2)= 0.44), with attitude (= 0.25), subjective norms (= 0.28) and perceived behavioral control (= 0.35) significant, and subsequent behavior (R(2) = 0.15, with intention (= 0.25) and perceived behavioral control (= 0.18) significant. Frequency of past behavior explained a significant, albeit small, amount of additional variance in intention (1 percent) and behavior (4 percent). The results indicate that the TPB is applicable to the prediction of food choice-related intention and behavior among young adult students living in a non-occidental setting.

Beliefs and Intentions for Skin Protection and Exposure

PubMed Central

Heckman, Carolyn J.; Manne, Sharon L.; Kloss, Jacqueline D.; Bass, Sarah Bauerle; Collins, Bradley; Lessin, Stuart R.

2010-01-01

Objectives To evaluate Fishbein’s Integrative Model in predicting young adults’ skin protection, sun exposure, and indoor tanning intentions. Methods 212 participants completed an online survey. Results Damage distress, self-efficacy, and perceived control accounted for 34% of the variance in skin protection intentions. Outcome beliefs and low self-efficacy for sun avoidance accounted for 25% of the variance in sun exposure intentions. Perceived damage, outcome evaluation, norms, and indoor tanning prototype accounted for 32% of the variance in indoor tanning intentions. Conclusions Future research should investigate whether these variables predict exposure and protection behaviors and whether intervening can reduce young adults’ skin cancer risk behaviors. PMID:22251761

Anosognosia, neglect, extinction and lesion site predict impairment of daily living after right-hemispheric stroke.

PubMed

Vossel, Simone; Weiss, Peter H; Eschenbeck, Philipp; Fink, Gereon R

2013-01-01

Right-hemispheric stroke can give rise to manifold neuropsychological deficits, in particular, impairments of spatial perception which are often accompanied by reduced self-awareness of these deficits (anosognosia). To date, the specific contribution of these deficits to a patient's difficulties in daily life activities remains to be elucidated. In 55 patients with right-hemispheric stroke we investigated the predictive value of different neglect-related symptoms, visual extinction and anosognosia for the performance of standardized activities of daily living (ADL). The additional impact of lesion location was examined using voxel-based lesion-symptom mapping. Step-wise linear regression revealed that anosognosia for visuospatial deficits was the most important predictor for performance in standardized ADL. In addition, motor-intentional and perceptual-attentional neglect, extinction and cancellation task performance significantly predicted ADL performance. Lesions comprising the right frontal and cingulate cortex and adjacent white matter explained additional variance in the performance of standardized ADL, in that damage to these areas was related to lower performance than predicted by the regression model only. Our data show a decisive role of anosognosia for visuospatial deficits for impaired ADL and therefore outcome/disability after stroke. The findings further demonstrate that the severity of neglect and extinction also predicts ADL performance. Our results thus strongly suggest that right-hemispheric stroke patients should not only be routinely assessed for neglect and extinction but also for anosognosia to initiate appropriate rehabilitative treatment. The observation that right frontal lesions explain additional variance in ADL most likely reflects that dysfunction of the supervisory system also significantly impacts upon rehabilitation. Copyright © 2012 Elsevier Ltd. All rights reserved.

Early post-stroke cognition in stroke rehabilitation patients predicts functional outcome at 13 months.

PubMed

Wagle, Jørgen; Farner, Lasse; Flekkøy, Kjell; Bruun Wyller, Torgeir; Sandvik, Leiv; Fure, Brynjar; Stensrød, Brynhild; Engedal, Knut

2011-01-01

To identify prognostic factors associated with functional outcome at 13 months in a sample of stroke rehabilitation patients. Specifically, we hypothesized that cognitive functioning early after stroke would predict long-term functional outcome independently of other factors. 163 stroke rehabilitation patients underwent a structured neuropsychological examination 2-3 weeks after hospital admittance, and their functional status was subsequently evaluated 13 months later with the modified Rankin Scale (mRS) as outcome measure. Three predictive models were built using linear regression analyses: a biological model (sociodemographics, apolipoprotein E genotype, prestroke vascular factors, lesion characteristics and neurological stroke-related impairment); a functional model (pre- and early post-stroke cognitive functioning, personal and instrumental activities of daily living, ADL, and depressive symptoms), and a combined model (including significant variables, with p value <0.05, from the biological and functional models). A combined model of 4 variables best predicted long-term functional outcome with explained variance of 49%: neurological impairment (National Institute of Health Stroke Scale; β = 0.402, p < 0.001), age (β = 0.233, p = 0.001), post-stroke cognitive functioning (Repeatable Battery of Neuropsychological Status, RBANS; β = -0.248, p = 0.001) and prestroke personal ADL (Barthel Index; β = -0.217, p = 0.002). Further linear regression analyses of which RBANS indexes and subtests best predicted long-term functional outcome showed that Coding (β = -0.484, p < 0.001) and Figure Copy (β = -0.233, p = 0.002) raw scores at baseline explained 42% of the variance in mRS scores at follow-up. Early post-stroke cognitive functioning as measured by the RBANS is a significant and independent predictor of long-term functional post-stroke outcome. Copyright © 2011 S. Karger AG, Basel.

Relationship between clinical fieldwork educator performance and health professional students' perceptions of their practice education learning environments.

PubMed

Brown, Ted; Williams, Brett; Lynch, Marty

2013-12-01

The Dundee Ready Education Environment Measure, Clinical Teaching Effectiveness Instrument, and Clinical Learning Environment Inventory were completed by 548 undergraduate students (54.5% response rate) enrolled in eight health professional bachelor degree courses. Regression analysis was used to investigate the significant predictors of the Clinical Teaching Effectiveness Instrument with the Dundee Ready Education Environment Measure and Clinical Learning Environment Inventory subscales as independent variables. The results indicated that the Dundee Ready Education Environment Measure and Clinical Learning Environment Inventory Actual version subscale scores explained 44% of the total variance in the Clinical Teaching Effectiveness Instrument score. The Dundee Ready Education Environment Measure subscale Academic Self-Perception explained 1.1% of the variance in the Clinical Teaching Effectiveness Instrument score. The Clinical Learning Environment Inventory Actual subscales accounted for the following variance percentages in the Clinical Teaching Effectiveness Instrument score: personalization, 1.1%; satisfaction, 1.7%; task orientation, 5.1%; and innovation, 6.2%. Aspects of the clinical learning environment appear to be predictive of the effectiveness of the clinical teaching that students experience. Fieldwork educator performance might be a significant contributing factor toward student skill development and practitioner success. © 2013 Wiley Publishing Asia Pty Ltd.

Critical thinking, educational preparation, and development of moral judgment among selected groups of practicing nurses.

PubMed

Ketefian, S

1981-01-01

The focus of this descriptive study was the relationship between critical thinking, educational preparation, and level of moral judgment in 79 practicing nurses. The Watson-Glaser Critical Thinking Appraisal Test was used to measure critical thinking; information on the participating nurses' educational preparation was obtained from a personal information sheet. Moral judgment was measured by Rest's Defining Issues Test. The hypothesis that critical thinking would be positively related to moral judgment was tested by Pearson product moment correlation; the obtained coefficient of .5326 was significant at the .001 level. The hypothesis that there would be a difference between professional and technical nurses' moral judgments was tested through a one-way analysis of variance. The F ratio (F [1,77] = 9.6) was significant beyond the .01 level. Data also supported the hypothesis that critical thinking and educational preparation would predict greater variance in moral judgment than either variable alone, which was tested through multiple regression analysis (F [2,75] = 18.3, p = .01). Critical thinking and education together accounted for 32.9 percent of the variance in moral judgment. Implications of the findings are discussed for nursing research, practice, and education.

Testing Small Variance Priors Using Prior-Posterior Predictive p Values.

PubMed

Hoijtink, Herbert; van de Schoot, Rens

2017-04-03

Muthén and Asparouhov (2012) propose to evaluate model fit in structural equation models based on approximate (using small variance priors) instead of exact equality of (combinations of) parameters to zero. This is an important development that adequately addresses Cohen's (1994) The Earth is Round (p < .05), which stresses that point null-hypotheses are so precise that small and irrelevant differences from the null-hypothesis may lead to their rejection. It is tempting to evaluate small variance priors using readily available approaches like the posterior predictive p value and the DIC. However, as will be shown, both are not suited for the evaluation of models based on small variance priors. In this article, a well behaving alternative, the prior-posterior predictive p value, will be introduced. It will be shown that it is consistent, the distributions under the null and alternative hypotheses will be elaborated, and it will be applied to testing whether the difference between 2 means and the size of a correlation are relevantly different from zero. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Post-mortem prediction of primal and selected retail cut weights of New Zealand lamb from carcass and animal characteristics.

PubMed

Ngo, L; Ho, H; Hunter, P; Quinn, K; Thomson, A; Pearson, G

2016-02-01

Post-mortem measurements (cold weight, grade and external carcass linear dimensions) as well as live animal data (age, breed, sex) were used to predict ovine primal and retail cut weights for 792 lamb carcases. Significant levels of variance could be explained using these predictors. The predictive power of those measurements on primal and retail cut weights was studied by using the results from principal component analysis and the absolute value of the t-statistics of the linear regression model. High prediction accuracy for primal cut weight was achieved (adjusted R(2) up to 0.95), as well as moderate accuracy for key retail cut weight: tenderloins (adj-R(2)=0.60), loin (adj-R(2)=0.62), French rack (adj-R(2)=0.76) and rump (adj-R(2)=0.75). The carcass cold weight had the best predictive power, with the accuracy increasing by around 10% after including the next three most significant variables. Copyright © 2015 Elsevier Ltd. All rights reserved.

Using Peer Injunctive Norms to Predict Early Adolescent Cigarette Smoking Intentions

PubMed Central

Zaleski, Adam C.; Aloise-Young, Patricia A.

2013-01-01

The present study investigated the importance of the perceived injunctive norm to predict early adolescent cigarette smoking intentions. A total of 271 6th graders completed a survey that included perceived prevalence of friend smoking (descriptive norm), perceptions of friends’ disapproval of smoking (injunctive norm), and future smoking intentions. Participants also listed their five best friends, in which the actual injunctive norm was calculated. Results showed that smoking intentions were significantly correlated with the perceived injunctive norm but not with the actual injunctive norm. Secondly, the perceived injunctive norm predicted an additional 3.4% of variance in smoking intentions above and beyond the perceived descriptive norm. These results demonstrate the importance of the perceived injunctive norm in predicting early adolescent smoking intentions. PMID:24078745

Specification of variables predictive of victories in the sport of boxing.

PubMed

Warnick, Jason E; Warnick, Kyla

2007-08-01

Compared to other sports, very little research has been conducted on which variables can predict victory in the sport of boxing. This investigation examined whether boxers' age, weight change from their preceding contest, country of origin, total number of wins, total number of losses, performance in their preceding contest, or the possession of a championship title was predictive of a winning performance in a given bout. A 1-mo. sample of male professional boxing records for all contests held in the USA (N = 400) were collected from the BoxRec online database. Logistic regression analysis indicated that only boxers' age, total number of wins and losses, and the performance in the preceding contest predicted significant variance in outcome.

Executive Functions as Predictors of School Performance and Social Relationships: Primary and Secondary School Students.

PubMed

Zorza, Juan Pablo; Marino, Julián; Acosta Mesas, Alberto

2016-05-12

This study examined the relationship between executive functions (EFs) and school performance in primary and secondary school students aged 8 to 13 years (N = 146, M = 10.4, 45.8% girls). EFs were evaluated using the Trail Making Test (TMT), Verbal Fluency (VF), and the Stroop Test. Students' GPAs and teachers' assessment of academic skills were used to measure school performance. To evaluate the students' social behavior, participants were asked to rate all their classmates' prosocial behavior and nominate three students with whom they preferred to do school activities; teachers also provided evaluations of students' social skills. EF measures explained 41% (p = .003, f 2 = .694) of variability in school performance and 29% (p = .005, f 2 = .401) of variance in social behavior in primary school students. The predictive power of EFs was found to be lower for secondary school students, although the TMT showed significant prediction and explained 13% (p = .004, f 2 = .149) of variance in school performance and 15% (p = .008, f 2 = .176) in peer ratings of prosocial behavior. This paper discusses the relevance of EFs in the school environment and their different predictive power in primary and secondary school students.

Brief report: understanding intention to be physically active and physical activity behaviour in adolescents from a low socio-economic status background: an application of the Theory of Planned Behaviour.

PubMed

Duncan, Michael J; Rivis, Amanda; Jordan, Caroline

2012-06-01

The aim of this brief report is to report on the utility of the Theory of Planned Behaviour (TPB) for predicting the physical activity intentions and behaviour of British adolescents from lower-than-average socio-economic backgrounds. A prospective questionnaire design was employed with 197, 13-14 year olds (76 males, 121 females). At time 1 participant completed standard measures of TPB variables. One week later (Time 2), participants completed the Physical Activity Questionnaire for Adolescents (PAQ-A) as a measure of physical activity behaviour. Hierarchical regression analyses showed that attitude and perceived behavioural control jointly accounted for 25% of the variance in intention (p = 0.0001). Perceived behavioural control emerged as the only significant predictor of physical activity behaviour and explained 3.7% of the variance (p = 0.001). Therefore, attitude and PBC successfully predicts intention towards physical activity and PBC predicts physical activity behaviour in British adolescents from lower-than-average socio-economic backgrounds. Copyright © 2011 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Metabolism, growth, and the energetic definition of fitness: a quantitative genetic study in the land snail Cornu aspersum.

PubMed

Bruning, Andrea; Gaitán-Espitia, Juan Diego; González, Avia; Bartheld, José Luis; Nespolo, Roberto F

2013-01-01

Life-history evolution-the way organisms allocate time and energy to reproduction, survival, and growth-is a central question in evolutionary biology. One of its main tenets, the allocation principle, predicts that selection will reduce energy costs of maintenance in order to divert energy to survival and reproduction. The empirical support for this principle is the existence of a negative relationship between fitness and metabolic rate, which has been observed in some ectotherms. In juvenile animals, a key function affecting fitness is growth rate, since fast growers will reproduce sooner and maximize survival. In principle, design constraints dictate that growth rate cannot be reduced without affecting maintenance costs. Hence, it is predicted that juveniles will show a positive relationship between fitness (growth rate) and metabolic rate, contrarily to what has been observed in adults. Here we explored this problem using land snails (Cornu aspersum). We estimated the additive genetic variance-covariance matrix for growth and standard metabolic rate (SMR; rate of CO2 production) using 34 half-sibling families. We measured eggs, hatchlings, and juveniles in 208 offspring that were isolated right after egg laying (i.e., minimizing maternal and common environmental variance). Surprisingly, our results showed that additive genetic effects (narrow-sense heritabilities, h(2)) and additive genetic correlations (rG) were small and nonsignificant. However, the nonadditive proportion of phenotypic variances and correlations (rC) were unexpectedly large and significant. In fact, nonadditive genetic effects were positive for growth rate and SMR ([Formula: see text]; [Formula: see text]), supporting the idea that fitness (growth rate) cannot be maximized without incurring maintenance costs. Large nonadditive genetic variances could result as a consequence of selection eroding the additive genetic component, which suggests that past selection could have produced nonadditive genetic correlation. It is predicted that this correlation is reduced when adulthood is attained and selection starts to promote the reduction in metabolic rate.

Modeling individual differences in text reading fluency: a different pattern of predictors for typically developing and dyslexic readers

PubMed Central

Zoccolotti, Pierluigi; De Luca, Maria; Marinelli, Chiara V.; Spinelli, Donatella

2014-01-01

This study was aimed at predicting individual differences in text reading fluency. The basic proposal included two factors, i.e., the ability to decode letter strings (measured by discrete pseudo-word reading) and integration of the various sub-components involved in reading (measured by Rapid Automatized Naming, RAN). Subsequently, a third factor was added to the model, i.e., naming of discrete digits. In order to use homogeneous measures, all contributing variables considered the entire processing of the item, including pronunciation time. The model, which was based on commonality analysis, was applied to data from a group of 43 typically developing readers (11- to 13-year-olds) and a group of 25 chronologically matched dyslexic children. In typically developing readers, both orthographic decoding and integration of reading sub-components contributed significantly to the overall prediction of text reading fluency. The model prediction was higher (from ca. 37 to 52% of the explained variance) when we included the naming of discrete digits variable, which had a suppressive effect on pseudo-word reading. In the dyslexic readers, the variance explained by the two-factor model was high (69%) and did not change when the third factor was added. The lack of a suppression effect was likely due to the prominent individual differences in poor orthographic decoding of the dyslexic children. Analyses on data from both groups of children were replicated by using patches of colors as stimuli (both in the RAN task and in the discrete naming task) obtaining similar results. We conclude that it is possible to predict much of the variance in text-reading fluency using basic processes, such as orthographic decoding and integration of reading sub-components, even without taking into consideration higher-order linguistic factors such as lexical, semantic and contextual abilities. The approach validity of using proximal vs. distal causes to predict reading fluency is discussed. PMID:25477856

Burnout among psychosocial oncologists: an application and extension of the effort–reward imbalance model

PubMed Central

Rasmussen, Victoria; Turnell, Adrienne; Butow, Phyllis; Juraskova, Ilona; Kirsten, Laura; Wiener, Lori; Patenaude, Andrea; Hoekstra-Weebers, Josette; Grassi, Luigi

2016-01-01

Objectives Burnout is a significant problem among healthcare professionals working within the oncology setting. This study aimed to investigate predictors of emotional exhaustion (EE) and depersonalisation (DP) in psychosocial oncologists, through the application of the effort–reward imbalance (ERI) model with an additional focus on the role of meaningful work in the burnout process. Methods Psychosocial oncology clinicians (n = 417) in direct patient contact who were proficient in English were recruited from 10 international psychosocial oncology societies. Participants completed an online questionnaire, which included measures of demographic and work characteristics, EE and DP subscales of the Maslach Burnout Inventory-Human Services Survey, the Short Version ERI Questionnaire and the Work and Meaning Inventory. Results Higher effort and lower reward were both significantly associated with greater EE, although not DP. The interaction of higher effort and lower reward did not predict greater EE or DP. Overcommitment predicted both EE and DP but did not moderate the impact of effort and reward on burnout. Overall, the ERI model accounted for 33% of the variance in EE. Meaningful work significantly predicted both EE and DP but accounted for only 2% more of the variance in EE above and beyond the ERI model. Conclusions The ERI was only partially supported as a useful framework for investigating burnout in psychosocial oncology professionals. Meaningful work may be a viable extension of the ERI model. Burnout among health professionals may be reduced by interventions aimed at increasing self-efficacy and changes to the supportive work environment. PMID:26239424

Anxiety Sensitivity Index (ASI-3) subscales predict unique variance in anxiety and depressive symptoms.

PubMed

Olthuis, Janine V; Watt, Margo C; Stewart, Sherry H

2014-03-01

Anxiety sensitivity (AS) has been implicated in the development and maintenance of a range of mental health problems. The development of the Anxiety Sensitivity Index - 3, a psychometrically sound index of AS, has provided the opportunity to better understand how the lower-order factors of AS - physical, psychological, and social concerns - are associated with unique forms of psychopathology. The present study investigated these associations among 85 treatment-seeking adults with high AS. Participants completed measures of AS, anxiety, and depression. Multiple regression analyses controlling for other emotional disorder symptoms revealed unique associations between AS subscales and certain types of psychopathology. Only physical concerns predicted unique variance in panic, only cognitive concerns predicted unique variance in depressive symptoms, and social anxiety was predicted by only social concerns. Findings emphasize the importance of considering the multidimensional nature of AS in understanding its role in anxiety and depression and their treatment. Copyright © 2013 Elsevier Ltd. All rights reserved.

Mixing Strong and Weak Targets Provides No Evidence against the Unequal-Variance Explanation of zRoc Slope: A Comment on Koen and Yonelinas (2010)

ERIC Educational Resources Information Center

Starns, Jeffrey J.; Rotello, Caren M.; Ratcliff, Roger

2012-01-01

Koen and Yonelinas (2010; K&Y) reported that mixing classes of targets that had short (weak) or long (strong) study times had no impact on zROC slope, contradicting the predictions of the encoding variability hypothesis. We show that they actually derived their predictions from a mixture unequal-variance signal detection (UVSD) model, which…

Predicting relatedness and self-definition depressive experiences in aging women based on personality traits: a preliminary study.

PubMed

Henriques-Calado, Joana; Duarte-Silva, Maria Eugénia; Campos, Rui C; Sacoto, Carlota; Keong, Ana Marta; Junqueira, Diana

2013-01-01

As part of the research relating personality and depression, this study seeks to predict depressive experiences in aging women according to Sidney Blatt's perspective based on the Five-Factor Model of Personality. The NEO-Five Factor Inventory and the Depressive Experiences Questionnaire were administered. The domains Neuroticism, Agreeableness, and Conscientiousness predicted self-criticism, explaining 68% of the variance; the domains Neuroticism and Extraversion predicted dependency, explaining 62% of the variance. The subfactors Neediness and Connectedness were differently related to personality traits. These findings are relevant to the research relating personality and anaclitic / introjective depressive experiences in late adulthood.

Evaluation of three statistical prediction models for forensic age prediction based on DNA methylation.

PubMed

Smeers, Inge; Decorte, Ronny; Van de Voorde, Wim; Bekaert, Bram

2018-05-01

DNA methylation is a promising biomarker for forensic age prediction. A challenge that has emerged in recent studies is the fact that prediction errors become larger with increasing age due to interindividual differences in epigenetic ageing rates. This phenomenon of non-constant variance or heteroscedasticity violates an assumption of the often used method of ordinary least squares (OLS) regression. The aim of this study was to evaluate alternative statistical methods that do take heteroscedasticity into account in order to provide more accurate, age-dependent prediction intervals. A weighted least squares (WLS) regression is proposed as well as a quantile regression model. Their performances were compared against an OLS regression model based on the same dataset. Both models provided age-dependent prediction intervals which account for the increasing variance with age, but WLS regression performed better in terms of success rate in the current dataset. However, quantile regression might be a preferred method when dealing with a variance that is not only non-constant, but also not normally distributed. Ultimately the choice of which model to use should depend on the observed characteristics of the data. Copyright © 2018 Elsevier B.V. All rights reserved.

Natural language processing in an intelligent writing strategy tutoring system.

PubMed

McNamara, Danielle S; Crossley, Scott A; Roscoe, Rod

2013-06-01

The Writing Pal is an intelligent tutoring system that provides writing strategy training. A large part of its artificial intelligence resides in the natural language processing algorithms to assess essay quality and guide feedback to students. Because writing is often highly nuanced and subjective, the development of these algorithms must consider a broad array of linguistic, rhetorical, and contextual features. This study assesses the potential for computational indices to predict human ratings of essay quality. Past studies have demonstrated that linguistic indices related to lexical diversity, word frequency, and syntactic complexity are significant predictors of human judgments of essay quality but that indices of cohesion are not. The present study extends prior work by including a larger data sample and an expanded set of indices to assess new lexical, syntactic, cohesion, rhetorical, and reading ease indices. Three models were assessed. The model reported by McNamara, Crossley, and McCarthy (Written Communication 27:57-86, 2010) including three indices of lexical diversity, word frequency, and syntactic complexity accounted for only 6% of the variance in the larger data set. A regression model including the full set of indices examined in prior studies of writing predicted 38% of the variance in human scores of essay quality with 91% adjacent accuracy (i.e., within 1 point). A regression model that also included new indices related to rhetoric and cohesion predicted 44% of the variance with 94% adjacent accuracy. The new indices increased accuracy but, more importantly, afford the means to provide more meaningful feedback in the context of a writing tutoring system.

Effects of education and word reading on cognitive scores in a community-based sample of Spanish elders with diverse socioeconomic status.

PubMed

Contador, Israel; Bermejo-Pareja, Félix; Del Ser, Teodoro; Benito-León, Julián

2015-01-01

The influence of education and oral word-reading ability on cognitive performance was examined in a sample of 1510 nondemented elders differing in socioeconomic status (SES) from three Spanish communities. All individuals were enrolled in the Neurological Disorders in Central Spain, a population-based epidemiological study in central Spain. They completed a detailed demographic survey and a short standardized neuropsychological battery assessing psychomotor speed, attention, language, and memory. The Word Accentuation Test (WAT) was used as measure of oral reading ability. The influence of education and oral reading on cognitive performance was determined by multiple linear regression models, first controlling for demographics (age and sex), and subsequently for the WAT score and education. The contribution of socioeconomic conditions was addressed by stratifying the sample into groups of high and low SES. The WAT showed a significant independent effect on cognitive scores, generally greater than that predicted by demographics. The higher predictive power of oral word reading on cognitive scores compared to education was consistent across the three communities. Although the variance explained by WAT was very similar in areas with diverse SES (low vs. high), WAT scores accounted for slightly more variance in naming and memory tasks in low SES areas. In contrast, the variance explained by WAT was higher for verbal fluency and the Trail-Making Test in areas with high SES. Oral word-reading ability predicts cognitive performance better than years of education across individuals with different SES. The influence of WAT may be modulated by SES and cognitive task properties.

An Examination of the Viability of Class Climate as a Useful Construct in Secondary Schools. A Study of Schooling in the United States. Technical Report Series, No. 23.

ERIC Educational Resources Information Center

Engstrom, Gerald A.

Classroom climate has been found to predict a significant portion of the variance in student achievement, independent of student background and intelligence quotient scores. This study sought to more clearly define classroom climate by determining to what extent climate measures teacher characteristics, student characteristics, and classroom…

Undergraduate Navigator Training Attrition Study

DTIC Science & Technology

1975-11-01

stabilization. The Masculinity- Feminity Scale (SVIB), significant at the .05 level, contributed 1.73% to the predicted variance. High scores (those...8217 a iiiftihlilfft-tMJ ^^mm^mmmwm^mmmmm mmmmm Do you have extensive experience in athletic competition? If so, what sport (s) and what kind of...machinery? For example, farm equipment, construction equipment. Do you have extensive experience in athletic competition? If so, what sport (s) and what

Data Analysis and Its Impact on Predicting Schedule & Cost Risk

DTIC Science & Technology

2006-03-01

variance of the error term by performing a Breusch - Pagan test for constant variance (Neter et al., 1996:239). In order to test the normality of...is constant variance. Using Microsoft Excel®, we calculate a p- 68 value of 0.225678 for the Breusch - Pagan test . We again compare this p-value to...calculate a p-value of 0.121211092 Breusch - Pagan test . We again compare this p-value to an alpha of 0.05 indicating our assumption of constant variance

Modeling Multiplicative Error Variance: An Example Predicting Tree Diameter from Stump Dimensions in Baldcypress

Treesearch

Bernard R. Parresol

1993-01-01

In the context of forest modeling, it is often reasonable to assume a multiplicative heteroscedastic error structure to the data. Under such circumstances ordinary least squares no longer provides minimum variance estimates of the model parameters. Through study of the error structure, a suitable error variance model can be specified and its parameters estimated. This...

A Study of Child Variance, Volume 4: The Future; Conceptual Project in Emotional Disturbance.

ERIC Educational Resources Information Center

Rhodes, William C.

Presented in the fourth volume in a series are a discussion of critical issues related to child variance and predictions for how society will perceive and respond to child variance in the future. Reviewed in an introductory chapter are the contents of the first three volumes which deal with conceptual models, interventions, and service delivery…

Associations among self-concept, verbal behaviors, and group climate early in the group counseling process.

PubMed

Jen Der Pan, Peter; Fan, Ai Chun; Bhat, Christine Suniti; Chang, Shona Shih Hua

2012-12-01

In this study, relations among group members' self-concept, verbal behaviors, and group climate early in the group counseling process were assessed for college students who were randomly assigned to four counseling groups. Based on measures from the hill interaction matrix, it was observed that family, social, and action self-concepts, as well as engagement, avoidance, and conflict group climate, were correlated with several verbal behaviors. Silence and quadrant 4 (Q4), which consists of speculative and confrontative verbal behaviors at personal and relationship levels, significantly predicted and explained 43% of the variance in engagement group climate. Silence and Q3, comprised of conventional and assertive verbal behaviors at personal and relationship levels, and Q1, conventional and assertive verbal behaviors at topic and group levels, explained 66% of variance in avoidance climate. Q4 and Silence explained 33% of conflict climate variance early in the group sessions. Implications for research and counseling practice are suggested.

Predicting Performance in Higher Education Using Proximal Predictors.

PubMed

Niessen, A Susan M; Meijer, Rob R; Tendeiro, Jorge N

2016-01-01

We studied the validity of two methods for predicting academic performance and student-program fit that were proximal to important study criteria. Applicants to an undergraduate psychology program participated in a selection procedure containing a trial-studying test based on a work sample approach, and specific skills tests in English and math. Test scores were used to predict academic achievement and progress after the first year, achievement in specific course types, enrollment, and dropout after the first year. All tests showed positive significant correlations with the criteria. The trial-studying test was consistently the best predictor in the admission procedure. We found no significant differences between the predictive validity of the trial-studying test and prior educational performance, and substantial shared explained variance between the two predictors. Only applicants with lower trial-studying scores were significantly less likely to enroll in the program. In conclusion, the trial-studying test yielded predictive validities similar to that of prior educational performance and possibly enabled self-selection. In admissions aimed at student-program fit, or in admissions in which past educational performance is difficult to use, a trial-studying test is a good instrument to predict academic performance.

Further study of terrain effects on the mesoscale spectrum of atmospheric motions

NASA Technical Reports Server (NTRS)

Jasperson, W. H.; Nastrom, G. D.; Fritts, D. C.

1990-01-01

Wind and temperature data collected on commercial airliners are used to investigate the effects of underlying terrain on mesoscale variability. These results expand upon those of Nastrom et al., by including all available data from the Global Atmospheric Sampling Program (GASP) and by more closely focusing on the coupling of variance with the roughness of the underlying terrain over mountainous regions. The earlier results, showing that variances are larger over mountains than over oceans or plains, with greatest increases at wavelengths below about 80 km, are confirmed. Statistical tests are used to confirm that these differences are highly significant. Over mountainous regions the roughness of the underlying terrain was parameterized from topographic data and it was found that variances are highly correlated with roughness and, in the troposphere, with background windspeed. Average variances over the roughest terrain areas range up to about ten times larger than those over the oceans. These results are found to follow the scaling with stability predicted in the framework of linenar gravity wave theory. The implications of these results for vertical transports of momentum and energy, assuming they are due to gravity waves and considering the effects of intermittency and anisotroy, are also discussed.

New Methods for Estimating Seasonal Potential Climate Predictability

NASA Astrophysics Data System (ADS)

Feng, Xia

This study develops two new statistical approaches to assess the seasonal potential predictability of the observed climate variables. One is the univariate analysis of covariance (ANOCOVA) model, a combination of autoregressive (AR) model and analysis of variance (ANOVA). It has the advantage of taking into account the uncertainty of the estimated parameter due to sampling errors in statistical test, which is often neglected in AR based methods, and accounting for daily autocorrelation that is not considered in traditional ANOVA. In the ANOCOVA model, the seasonal signals arising from external forcing are determined to be identical or not to assess any interannual variability that may exist is potentially predictable. The bootstrap is an attractive alternative method that requires no hypothesis model and is available no matter how mathematically complicated the parameter estimator. This method builds up the empirical distribution of the interannual variance from the resamplings drawn with replacement from the given sample, in which the only predictability in seasonal means arises from the weather noise. These two methods are applied to temperature and water cycle components including precipitation and evaporation, to measure the extent to which the interannual variance of seasonal means exceeds the unpredictable weather noise compared with the previous methods, including Leith-Shukla-Gutzler (LSG), Madden, and Katz. The potential predictability of temperature from ANOCOVA model, bootstrap, LSG and Madden exhibits a pronounced tropical-extratropical contrast with much larger predictability in the tropics dominated by El Nino/Southern Oscillation (ENSO) than in higher latitudes where strong internal variability lowers predictability. Bootstrap tends to display highest predictability of the four methods, ANOCOVA lies in the middle, while LSG and Madden appear to generate lower predictability. Seasonal precipitation from ANOCOVA, bootstrap, and Katz, resembling that for temperature, is more predictable over the tropical regions, and less predictable in extropics. Bootstrap and ANOCOVA are in good agreement with each other, both methods generating larger predictability than Katz. The seasonal predictability of evaporation over land bears considerably similarity with that of temperature using ANOCOVA, bootstrap, LSG and Madden. The remote SST forcing and soil moisture reveal substantial seasonality in their relations with the potentially predictable seasonal signals. For selected regions, either SST or soil moisture or both shows significant relationships with predictable signals, hence providing indirect insight on slowly varying boundary processes involved to enable useful seasonal climate predication. A multivariate analysis of covariance (MANOCOVA) model is established to identify distinctive predictable patterns, which are uncorrelated with each other. Generally speaking, the seasonal predictability from multivariate model is consistent with that from ANOCOVA. Besides unveiling the spatial variability of predictability, MANOCOVA model also reveals the temporal variability of each predictable pattern, which could be linked to the periodic oscillations.

Radiomics-based Prognosis Analysis for Non-Small Cell Lung Cancer

NASA Astrophysics Data System (ADS)

Zhang, Yucheng; Oikonomou, Anastasia; Wong, Alexander; Haider, Masoom A.; Khalvati, Farzad

2017-04-01

Radiomics characterizes tumor phenotypes by extracting large numbers of quantitative features from radiological images. Radiomic features have been shown to provide prognostic value in predicting clinical outcomes in several studies. However, several challenges including feature redundancy, unbalanced data, and small sample sizes have led to relatively low predictive accuracy. In this study, we explore different strategies for overcoming these challenges and improving predictive performance of radiomics-based prognosis for non-small cell lung cancer (NSCLC). CT images of 112 patients (mean age 75 years) with NSCLC who underwent stereotactic body radiotherapy were used to predict recurrence, death, and recurrence-free survival using a comprehensive radiomics analysis. Different feature selection and predictive modeling techniques were used to determine the optimal configuration of prognosis analysis. To address feature redundancy, comprehensive analysis indicated that Random Forest models and Principal Component Analysis were optimum predictive modeling and feature selection methods, respectively, for achieving high prognosis performance. To address unbalanced data, Synthetic Minority Over-sampling technique was found to significantly increase predictive accuracy. A full analysis of variance showed that data endpoints, feature selection techniques, and classifiers were significant factors in affecting predictive accuracy, suggesting that these factors must be investigated when building radiomics-based predictive models for cancer prognosis.

Computationally efficient confidence intervals for cross-validated area under the ROC curve estimates.

PubMed

LeDell, Erin; Petersen, Maya; van der Laan, Mark

In binary classification problems, the area under the ROC curve (AUC) is commonly used to evaluate the performance of a prediction model. Often, it is combined with cross-validation in order to assess how the results will generalize to an independent data set. In order to evaluate the quality of an estimate for cross-validated AUC, we obtain an estimate of its variance. For massive data sets, the process of generating a single performance estimate can be computationally expensive. Additionally, when using a complex prediction method, the process of cross-validating a predictive model on even a relatively small data set can still require a large amount of computation time. Thus, in many practical settings, the bootstrap is a computationally intractable approach to variance estimation. As an alternative to the bootstrap, we demonstrate a computationally efficient influence curve based approach to obtaining a variance estimate for cross-validated AUC.

Interpersonal Problems and Their Relationship to Depression, Self-Esteem, and Malignant Self-Regard.

PubMed

Huprich, Steven K; Lengu, Ketrin; Evich, Carly

2016-12-01

DSM-5 Section III recommends that level of personality functioning be assessed. This requires an assessment of self and other representations. Malignant self-regard (MSR) is a way of assessing the level of functioning of those with a masochistic, self-defeating, depressive, or vulnerably narcissistic personality. In Study 1, 840 undergraduates were assessed for MSR, depressive symptoms, self-esteem, anaclitic and introjective depression, and interpersonal problems. MSR, self-esteem, depressive symptoms, and anaclitic and introjective depression were correlated with multiple dimensions of interpersonal problems, and MSR predicted the most variance in interpersonal scales measuring social inhibition, nonassertion, over-accommodation, and excessive self-sacrifice. MSR, anaclitic, and introjective depression predicted unique variance in six of the eight domains of interpersonal problems assessed. In Study 2, 68 undergraduates were provided positive or negative feedback. Consistent with theory, MSR predicted unique variance in state anxiety but not state anger. Results support the validity of the MSR construct.

Computationally efficient confidence intervals for cross-validated area under the ROC curve estimates

PubMed Central

Petersen, Maya; van der Laan, Mark

2015-01-01

In binary classification problems, the area under the ROC curve (AUC) is commonly used to evaluate the performance of a prediction model. Often, it is combined with cross-validation in order to assess how the results will generalize to an independent data set. In order to evaluate the quality of an estimate for cross-validated AUC, we obtain an estimate of its variance. For massive data sets, the process of generating a single performance estimate can be computationally expensive. Additionally, when using a complex prediction method, the process of cross-validating a predictive model on even a relatively small data set can still require a large amount of computation time. Thus, in many practical settings, the bootstrap is a computationally intractable approach to variance estimation. As an alternative to the bootstrap, we demonstrate a computationally efficient influence curve based approach to obtaining a variance estimate for cross-validated AUC. PMID:26279737

Numerical prediction of a draft tube flow taking into account uncertain inlet conditions

NASA Astrophysics Data System (ADS)

Brugiere, O.; Balarac, G.; Corre, C.; Metais, O.; Flores, E.; Pleroy

2012-11-01

The swirling turbulent flow in a hydroturbine draft tube is computed with a non-intrusive uncertainty quantification (UQ) method coupled to Reynolds-Averaged Navier-Stokes (RANS) modelling in order to take into account in the numerical prediction the physical uncertainties existing on the inlet flow conditions. The proposed approach yields not only mean velocity fields to be compared with measured profiles, as is customary in Computational Fluid Dynamics (CFD) practice, but also variance of these quantities from which error bars can be deduced on the computed profiles, thus making more significant the comparison between experiment and computation.

Investigating Predictors of Spelling Ability for Adults with Low Literacy Skills

PubMed Central

Talwar, Amani; Cote, Nicole Gilbert; Binder, Katherine S.

2014-01-01

This study examined whether the spelling abilities of adults with low literacy skills could be predicted by their phonological, orthographic, and morphological awareness. Sixty Adult Basic Education (ABE) students completed several literacy tasks. It was predicted that scores on phonological and orthographic tasks would explain variance in spelling scores, whereas scores on morphological tasks may not. Scores on all phonological tasks and on one orthographic task emerged as significant predictors of spelling scores. Additionally, error analyses revealed a limited influence of morphological knowledge in spelling attempts. Implications for ABE instruction are discussed. PMID:25364644

Bilateral versus unilateral cochlear implants in children: a study of spoken language outcomes.

PubMed

Sarant, Julia; Harris, David; Bennet, Lisa; Bant, Sharyn

2014-01-01

Although it has been established that bilateral cochlear implants (CIs) offer additional speech perception and localization benefits to many children with severe to profound hearing loss, whether these improved perceptual abilities facilitate significantly better language development has not yet been clearly established. The aims of this study were to compare language abilities of children having unilateral and bilateral CIs to quantify the rate of any improvement in language attributable to bilateral CIs and to document other predictors of language development in children with CIs. The receptive vocabulary and language development of 91 children was assessed when they were aged either 5 or 8 years old by using the Peabody Picture Vocabulary Test (fourth edition), and either the Preschool Language Scales (fourth edition) or the Clinical Evaluation of Language Fundamentals (fourth edition), respectively. Cognitive ability, parent involvement in children's intervention or education programs, and family reading habits were also evaluated. Language outcomes were examined by using linear regression analyses. The influence of elements of parenting style, child characteristics, and family background as predictors of outcomes were examined. Children using bilateral CIs achieved significantly better vocabulary outcomes and significantly higher scores on the Core and Expressive Language subscales of the Clinical Evaluation of Language Fundamentals (fourth edition) than did comparable children with unilateral CIs. Scores on the Preschool Language Scales (fourth edition) did not differ significantly between children with unilateral and bilateral CIs. Bilateral CI use was found to predict significantly faster rates of vocabulary and language development than unilateral CI use; the magnitude of this effect was moderated by child age at activation of the bilateral CI. In terms of parenting style, high levels of parental involvement, low amounts of screen time, and more time spent by adults reading to children facilitated significantly better vocabulary and language outcomes. In terms of child characteristics, higher cognitive ability and female sex were predictive of significantly better language outcomes. When family background factors were examined, having tertiary-educated primary caregivers and a family history of hearing loss were significantly predictive of better outcomes. Birth order was also found to have a significant negative effect on both vocabulary and language outcomes, with each older sibling predicting a 5 to 10% decrease in scores. Children with bilateral CIs achieved significantly better vocabulary outcomes, and 8-year-old children with bilateral CIs had significantly better language outcomes than did children with unilateral CIs. These improvements were moderated by children's ages at both first and second CIs. The outcomes were also significantly predicted by a number of factors related to parenting, child characteristics, and family background. Fifty-one percent of the variance in vocabulary outcomes and between 59 to 69% of the variance in language outcomes was predicted by the regression models.

The Theory of Planned Behavior as a Predictor of HIV Testing Intention.

PubMed

Ayodele, Olabode

2017-03-01

This investigation tests the theory of planned behavior (TPB) as a predictor of HIV testing intention among Nigerian university undergraduate students. A cross-sectional study of 392 students was conducted using a self-administered structured questionnaire that measured socio-demographics, perceived risk of human immunodeficiency virus (HIV) infection, and TPB constructs. Analysis was based on 273 students who had never been tested for HIV. Hierarchical multiple regression analysis assessed the applicability of the TPB in predicting HIV testing intention and additional predictive value of perceived risk of HIV infection. The prediction model containing TPB constructs explained 35% of the variance in HIV testing intention, with attitude and perceived behavioral control making significant and unique contributions to intention. Perceived risk of HIV infection contributed marginally (2%) but significantly to the final prediction model. Findings supported the TPB in predicting HIV testing intention. Although future studies must determine the generalizability of these results, the findings highlight the importance of perceived behavioral control, attitude, and perceived risk of HIV infection in the prediction of HIV testing intention among students who have not previously tested for HIV.

Progress Toward Improving Jet Noise Predictions in Hot Jets

NASA Technical Reports Server (NTRS)

Khavaran, Abbas; Kenzakowski, Donald C.

2007-01-01

An acoustic analogy methodology for improving noise predictions in hot round jets is presented. Past approaches have often neglected the impact of temperature fluctuations on the predicted sound spectral density, which could be significant for heated jets, and this has yielded noticeable acoustic under-predictions in such cases. The governing acoustic equations adopted here are a set of linearized, inhomogeneous Euler equations. These equations are combined into a single third order linear wave operator when the base flow is considered as a locally parallel mean flow. The remaining second-order fluctuations are regarded as the equivalent sources of sound and are modeled. It is shown that the hot jet effect may be introduced primarily through a fluctuating velocity/enthalpy term. Modeling this additional source requires specialized inputs from a RANS-based flowfield simulation. The information is supplied using an extension to a baseline two equation turbulence model that predicts total enthalpy variance in addition to the standard parameters. Preliminary application of this model to a series of unheated and heated subsonic jets shows significant improvement in the acoustic predictions at the 90 degree observer angle.

Job embeddedness and nurse retention.

PubMed

Reitz, O Ed; Anderson, Mary Ann; Hill, Pamela D

2010-01-01

Nurse retention is a different way of conceptualizing the employer-employee relationship when compared with turnover. Job embeddedness (JE), a construct based on retention, represents the sum of reasons why employees remain at their jobs. However, JE has not been investigated in relation to locale (urban or rural) or exclusively with a sample of registered nurses (RNs). The purpose of this study was to determine what factors (JE, age, gender, locale, and income) help predict nurse retention. A cross-sectional mailed survey design was used with RNs in different locales (urban or rural). Job embeddedness was measured by the score on the composite, standardized instrument. Nurse retention was measured by self-report items concerning intent to stay. A response rate of 49.3% was obtained. The typical respondent was female (96.1%), white, non-Hispanic (87.4%), and married (74.9%). Age and JE were predictive of nurse retention and accounted for 26% of the explained variance in intent to stay. Although age was a significant predictor of intent to stay, it accounted for only 1.4% of the variance while JE accounted for 24.6% of the variance of nurse retention (as measured by intent to stay). Older, more "embedded" nurses are more likely to remain employed in their current organization. Based on these findings, JE may form the basis for the development of an effective nurse retention program.

Aerobic fitness, maturation, and training experience in youth basketball.

PubMed

Carvalho, Humberto M; Coelho-e-Silva, Manuel J; Eisenmann, Joey C; Malina, Robert M

2013-07-01

Relationships among chronological age (CA), maturation, training experience, and body dimensions with peak oxygen uptake (VO2max) were considered in male basketball players 14-16 y of age. Data for all players included maturity status estimated as percentage of predicted adult height attained at the time of the study (Khamis-Roche protocol), years of training, body dimensions, and VO2max (incremental maximal test on a treadmill). Proportional allometric models derived from stepwise regressions were used to incorporate either CA or maturity status and to incorporate years of formal training in basketball. Estimates for size exponents (95% CI) from the separate allometric models for VO2max were height 2.16 (1.23-3.09), body mass 0.65 (0.37-0.93), and fat-free mass 0.73 (0.46-1.02). Body dimensions explained 39% to 44% of variance. The independent variables in the proportional allometric models explained 47% to 60% of variance in VO2max. Estimated maturity status (11-16% of explained variance) and training experience (7-11% of explained variance) were significant predictors with either body mass or estimated fat-free mass (P ≤ .01) but not with height. Biological maturity status and training experience in basketball had a significant contribution to VO2max via body mass and fat-free fat mass and also had an independent positive relation with aerobic performance. The results highlight the importance of considering variation associated with biological maturation in aerobic performance of late-adolescent boys.

Predicting Persuasion-Induced Behavior Change from the Brain

PubMed Central

Falk, Emily B.; Berkman, Elliot T.; Mann, Traci; Harrison, Brittany; Lieberman, Matthew D.

2011-01-01

Although persuasive messages often alter people’s self-reported attitudes and intentions to perform behaviors, these self-reports do not necessarily predict behavior change. We demonstrate that neural responses to persuasive messages can predict variability in behavior change in the subsequent week. Specifically, an a priori region of interest (ROI) in medial prefrontal cortex (MPFC) was reliably associated with behavior change (r = 0.49, p < 0.05). Additionally, an iterative cross-validation approach using activity in this MPFC ROI predicted an average 23% of the variance in behavior change beyond the variance predicted by self-reported attitudes and intentions. Thus, neural signals can predict behavioral changes that are not predicted from self-reported attitudes and intentions alone. Additionally, this is the first functional magnetic resonance imaging study to demonstrate that a neural signal can predict complex real world behavior days in advance. PMID:20573889

Evidence that specific executive functions predict symptom variance among schizophrenia patients with a predominantly negative symptom profile.

PubMed

Donohoe, Gary; Corvin, Aiden; Robertson, Ian H

2006-01-01

Although deficits in executive functioning in schizophrenia have been consistently reported, their precise relationship to symptomatology remains unclear. Recent approaches to executive functioning in nonschizophrenia studies have aimed to "fractionate" the individual cognitive processes involved. In this study, we hypothesised that if these processes are fractionable, then particular symptom syndromes may be selectively related to executive deficits. In particular, it was hoped that this approach could clarify whether negative and positive symptoms of schizophrenia are differentially related to particular aspects of executive/attentional functions. A total of 32 patients with schizophrenia and 16 matched controls were assessed on a series of tasks designed to tap the theoretically derived executive functions of Inhibition, Shifting set, Working memory, and Sustained attention. Negative symptoms were significantly predicted by performance on an "Inhibition" task (Stroop), and not by performance on any other task. Furthermore, for a subgroup of patients with predominantly negative symptoms variance in positive symptoms was only significantly predicted by performance on a set-shifting task (Visual Elevator), and not by performance on other tasks, including inhibition. Our results support the contention that negative symptoms can, at least partly, be conceived of as cognitive behaviours expressing specific executive deficits. Specifically, we discuss the possibility that negative symptoms may, in part, express a failure in response monitoring. We further suggest that the disordered metacognition resulting in positive symptoms may be mediated by cognitive flexibility in patients with a predominantly negative symptom profile.

Predicting Intentional Communication in Preverbal Preschoolers with Autism Spectrum Disorder.

PubMed

Sandbank, Micheal; Woynaroski, Tiffany; Watson, Linda R; Gardner, Elizabeth; Keçeli Kaysili, Bahar; Yoder, Paul

2017-06-01

Intentional communication has previously been identified as a value-added predictor of expressive language in preverbal preschoolers with autism spectrum disorder. In the present study, we sought to identify value-added predictors of intentional communication. Of five theoretically-motivated putative predictors of intentional communication measured early in the study (at study entry and 4 months after), three had significant zero-order correlations with later intentional communication (12 months after study entry) and were thus added to a linear model that predicted later intentional communication scores controlling for initial intentional communication scores at study entry. After controlling for initial intentional communication, early motor imitation was the only predictor that accounted for a significant amount of variance in children's later intentional communication.

Interrelationships among invasive and non-invasive indicators of biological maturation in adolescent male soccer players.

PubMed

Malina, Robert M; Coelho E Silva, Manuel J; Figueiredo, António J; Carling, Christopher; Beunen, Gaston P

2012-01-01

The relationships among indicators of biological maturation were evaluated and concordance between classifications of maturity status in two age groups of youth soccer players examined (11-12 years, n = 87; 13-14 years, n = 93). Data included chronological age (CA), skeletal age (SA, Fels method), stage of pubic hair, predicted age at peak height velocity, and percent of predicted adult height. Players were classified as on time, late or early in maturation using the SA-CA difference, predicted age at peak height velocity, and percent of predicted mature height. Factor analyses indicated two factors in players aged 11-12 years (maturity status: percent of predicted mature height, stage of pubic hair, 59% of variance; maturity timing: SA/CA ratio, predicted age at peak height velocity, 26% of variance), and one factor in players aged 13-14 years (68% of variance). Kappa coefficients were low (0.02-0.23) and indicated poor agreement between maturity classifications. Spearman rank-order correlations between categories were low to moderate (0.16-0.50). Although the indicators were related, concordance of maturity classifications between skeletal age and predicted age at peak height velocity and percent predicted mature height was poor. Talent development programmes call for the classification of youth as early, average, and late maturing for the purpose of designing training and competition programmes. Non-invasive indicators of maturity status have limitations for this purpose.

Personal and Environmental Characteristics Predicting Burnout Among Certified Athletic Trainers at National Collegiate Athletic Association Institutions

PubMed Central

Kania, Michelle L; Meyer, Barbara B; Ebersole, Kyle T

2009-01-01

Context: Recent research in the health care professions has shown that specific personal and environmental characteristics can predict burnout, which is a negative coping strategy related to stressful situations. Burnout has been shown to result in physiologic (eg, headaches, difficulty sleeping, poor appetite), psychological (eg, increased negative self-talk, depression, difficulty in interpersonal relationships), and behavioral (eg, diminished care, increased absenteeism, attrition) symptoms. Objective: To examine the relationship between selected personal and environmental characteristics and burnout among certified athletic trainers (ATs). Design: Cross-sectional survey. Setting: A demographic survey that was designed for this study and the Maslach Burnout Inventory–Human Services Survey. Patients or Other Participants: A total of 206 ATs employed at National Collegiate Athletic Association (NCAA) institutions as clinical ATs volunteered. Main Outcome Measure(s): We assessed personal and environmental characteristics of ATs with the demographic survey and measured burnout using the Maslach Burnout Inventory–Human Services Survey. Multiple regression analyses were performed to examine relationships between specific personal and environmental characteristics and each of the 3 subscales of burnout (emotional exhaustion, depersonalization, personal accomplishment). Results: Most ATs we surveyed experienced low to average levels of burnout. Personal characteristics predicted 45.5% of the variance in emotional exhaustion (P < .001), 21.5% of the variance in depersonalization (P < .001), and 24.8% of the variance in personal accomplishment (P < .001). Environmental characteristics predicted 16.7% of the variance in emotional exhaustion (P  =  .005), 14.4% of the variance in depersonalization (P  =  .024), and 10.4% of the variance in personal accomplishment (P  =  .209). Stress level and coaches' pressure to medically clear athletes predicted ratings on all 3 subscales of burnout. Conclusions: Our findings were similar to those of other studies of burnout among NCAA Division I ATs, coaches, and coach-teachers. The results also support the Cognitive-Affective Model of Athletic Burnout proposed by Smith. Finally, these results indicate new areas of concentration for burnout research and professional practice. PMID:19180220

A multivariate analysis of genetic variation in the advertisement call of the gray treefrog, Hyla versicolor.

PubMed

Welch, Allison M; Smith, Michael J; Gerhardt, H Carl

2014-06-01

Genetic variation in sexual displays is crucial for an evolutionary response to sexual selection, but can be eroded by strong selection. Identifying the magnitude and sources of additive genetic variance underlying sexually selected traits is thus an important issue in evolutionary biology. We conducted a quantitative genetics experiment with gray treefrogs (Hyla versicolor) to investigate genetic variances and covariances among features of the male advertisement call. Two energetically expensive traits showed significant genetic variation: call duration, expressed as number of pulses per call, and call rate, represented by its inverse, call period. These two properties also showed significant genetic covariance, consistent with an energetic constraint to call production. Combining the genetic variance-covariance matrix with previous estimates of directional sexual selection imposed by female preferences predicts a limited increase in call duration but no change in call rate despite significant selection on both traits. In addition to constraints imposed by the genetic covariance structure, an evolutionary response to sexual selection may also be limited by high energetic costs of long-duration calls and by preferences that act most strongly against very short-duration calls. Meanwhile, the persistence of these preferences could be explained by costs of mating with males with especially unattractive calls. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Habitat islands and the equilibrium theory of island biogeography: testing some predictions

USGS Publications Warehouse

Brown, M.; Dinsmore, J.J.

1988-01-01

Species-area data from a study of marsh birds are used to test five predictions generated by the equilibrium theory of island biogeography. Three predictions are supported: we found a significant species-area relationship, a non-zero level of turnover, and a variance-mean ratio of 0.5. One prediction is rejected: the extinction rates were not greater on small islands. The results of one test are equivocal: the number of species on each island was not always the same. As Gilbert (1980) suggests, a strong species-area relationship alone does not validate the theory. The avian communities we studied were on habitat islands, not true islands, and underwent complete extinction annually. Thus caution must be used before applying the theory to these and other habitat islands.

Using self-reported and objective measures of self-control to predict exercise and academic behaviors among first-year university students.

PubMed

Stork, Matthew J; Graham, Jeffrey D; Bray, Steven R; Martin Ginis, Kathleen A

2017-07-01

Thirty students (mean age = 18 ± 0.5 years) completed self-report (Self-Control Scale) and objective (isometric handgrip squeeze performance) measures of self-control, provided their exercise and academic (study/schoolwork) plans for the next month, and then logged these behaviors over the subsequent 4-week period. Trait self-control predicted exercise and academic behavior. Handgrip squeeze performance predicted academic behavior and adherence to academic plans. Further, regression analysis revealed that trait self-control and handgrip performance explained significant variance in academic behavior. These findings provide a new understanding of how different self-control measures can be used to predict first-year students' participation in, and adherence to, exercise and academic behaviors concurrently.

Predicting Well-being Longitudinally for Mothers Rearing Offspring with Intellectual and Developmental Disabilities

PubMed Central

Grein, Katherine A.; Glidden, Laraine Masters

2014-01-01

Background Well-being outcomes for parents of children with intellectual and developmental disabilities (IDD) may vary from positive to negative at different times and for different measures of well-being. Predicting and explaining this variability has been a major focus of family research for reasons that have both theoretical and applied implications. Methods The current study used data from a 23-year longitudinal investigation of adoptive and birth parents of children with IDD to determine which early child, mother, and family characteristics would predict the variance in maternal outcomes 20 years after their original measurement. Using hierarchical regression analyses, we tested the predictive power of variables measured when children were 7 years old on outcomes of maternal well-being when children were 26 years old. Outcome variables included maternal self-report measures of depression and well–being. Results Final models of well-being accounted for 20% to 34% of variance. For most outcomes, Family Accord and/or the personality variable of Neuroticism (emotional stability/instability) were significant predictors, but some variables demonstrated a different pattern. Conclusions These findings confirm that 1) Characteristics of the child, mother, and family during childhood can predict outcomes of maternal well-being 20 years later; and 2) Different predictor-outcome relationships can vary substantially, highlighting the importance of using multiple measures to gain a more comprehensive understanding of maternal well-being. These results have implications for refining prognoses for parents and for tailoring service delivery to individual child, parent, and family characteristics. PMID:25185956

Maternal risk factors predicting child physical characteristics and dysmorphology in fetal alcohol syndrome and partial fetal alcohol syndrome.

PubMed

May, Philip A; Tabachnick, Barbara G; Gossage, J Phillip; Kalberg, Wendy O; Marais, Anna-Susan; Robinson, Luther K; Manning, Melanie; Buckley, David; Hoyme, H Eugene

2011-12-01

Previous research in South Africa revealed very high rates of fetal alcohol syndrome (FAS), of 46-89 per 1000 among young children. Maternal and child data from studies in this community summarize the multiple predictors of FAS and partial fetal alcohol syndrome (PFAS). Sequential regression was employed to examine influences on child physical characteristics and dysmorphology from four categories of maternal traits: physical, demographic, childbearing, and drinking. Then, a structural equation model (SEM) was constructed to predict influences on child physical characteristics. Individual sequential regressions revealed that maternal drinking measures were the most powerful predictors of a child's physical anomalies (R² = .30, p < .001), followed by maternal demographics (R² = .24, p < .001), maternal physical characteristics (R²=.15, p < .001), and childbearing variables (R² = .06, p < .001). The SEM utilized both individual variables and the four composite categories of maternal traits to predict a set of child physical characteristics, including a total dysmorphology score. As predicted, drinking behavior is a relatively strong predictor of child physical characteristics (β = 0.61, p < .001), even when all other maternal risk variables are included; higher levels of drinking predict child physical anomalies. Overall, the SEM model explains 62% of the variance in child physical anomalies. As expected, drinking variables explain the most variance. But this highly controlled estimation of multiple effects also reveals a significant contribution played by maternal demographics and, to a lesser degree, maternal physical and childbearing variables. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Self-Assessed Hearing Handicap in Older Adults With Poorer-Than-Predicted Speech Recognition in Noise.

PubMed

Eckert, Mark A; Matthews, Lois J; Dubno, Judy R

2017-01-01

Even older adults with relatively mild hearing loss report hearing handicap, suggesting that hearing handicap is not completely explained by reduced speech audibility. We examined the extent to which self-assessed ratings of hearing handicap using the Hearing Handicap Inventory for the Elderly (HHIE; Ventry & Weinstein, 1982) were significantly associated with measures of speech recognition in noise that controlled for differences in speech audibility. One hundred sixty-two middle-aged and older adults had HHIE total scores that were significantly associated with audibility-adjusted measures of speech recognition for low-context but not high-context sentences. These findings were driven by HHIE items involving negative feelings related to communication difficulties that also captured variance in subjective ratings of effort and frustration that predicted speech recognition. The average pure-tone threshold accounted for some of the variance in the association between the HHIE and audibility-adjusted speech recognition, suggesting an effect of central and peripheral auditory system decline related to elevated thresholds. The accumulation of difficult listening experiences appears to produce a self-assessment of hearing handicap resulting from (a) reduced audibility of stimuli, (b) declines in the central and peripheral auditory system function, and (c) additional individual variation in central nervous system function.

Self-Assessed Hearing Handicap in Older Adults With Poorer-Than-Predicted Speech Recognition in Noise

PubMed Central

Matthews, Lois J.; Dubno, Judy R.

2017-01-01

Purpose Even older adults with relatively mild hearing loss report hearing handicap, suggesting that hearing handicap is not completely explained by reduced speech audibility. Method We examined the extent to which self-assessed ratings of hearing handicap using the Hearing Handicap Inventory for the Elderly (HHIE; Ventry & Weinstein, 1982) were significantly associated with measures of speech recognition in noise that controlled for differences in speech audibility. Results One hundred sixty-two middle-aged and older adults had HHIE total scores that were significantly associated with audibility-adjusted measures of speech recognition for low-context but not high-context sentences. These findings were driven by HHIE items involving negative feelings related to communication difficulties that also captured variance in subjective ratings of effort and frustration that predicted speech recognition. The average pure-tone threshold accounted for some of the variance in the association between the HHIE and audibility-adjusted speech recognition, suggesting an effect of central and peripheral auditory system decline related to elevated thresholds. Conclusion The accumulation of difficult listening experiences appears to produce a self-assessment of hearing handicap resulting from (a) reduced audibility of stimuli, (b) declines in the central and peripheral auditory system function, and (c) additional individual variation in central nervous system function. PMID:28060993

MANUSCRIPT IN PRESS: DEMENTIA & GERIATRIC COGNITIVE DISORDERS

PubMed Central

O’Bryant, Sid E.; Xiao, Guanghua; Barber, Robert; Cullum, C. Munro; Weiner, Myron; Hall, James; Edwards, Melissa; Grammas, Paula; Wilhelmsen, Kirk; Doody, Rachelle; Diaz-Arrastia, Ramon

2015-01-01

Background Prior work on the link between blood-based biomarkers and cognitive status has largely been based on dichotomous classifications rather than detailed neuropsychological functioning. The current project was designed to create serum-based biomarker algorithms that predict neuropsychological test performance. Methods A battery of neuropsychological measures was administered. Random forest analyses were utilized to create neuropsychological test-specific biomarker risk scores in a training set that were entered into linear regression models predicting the respective test scores in the test set. Serum multiplex biomarker data were analyzed on 108 proteins from 395 participants (197 AD cases and 198 controls) from the Texas Alzheimer’s Research and Care Consortium. Results The biomarker risk scores were significant predictors (p<0.05) of scores on all neuropsychological tests. With the exception of premorbid intellectual status (6.6%), the biomarker risk scores alone accounted for a minimum of 12.9% of the variance in neuropsychological scores. Biomarker algorithms (biomarker risk scores + demographics) accounted for substantially more variance in scores. Review of the variable importance plots indicated differential patterns of biomarker significance for each test, suggesting the possibility of domain-specific biomarker algorithms. Conclusions Our findings provide proof-of-concept for a novel area of scientific discovery, which we term “molecular neuropsychology.” PMID:24107792

Examining Women's Alcohol Consumption: The Theory of Planned Behavior and Self-Identity.

PubMed

Haydon, Helen M; Obst, Patricia L; Lewis, Ioni

2018-01-02

Changing trends demonstrate that women, in several economically developed countries, are drinking at higher levels than ever before. This study applied an extended Theory of Planned Behavior (TPB), including self-identity, to examine women's intentions to consume alcohol. Women (N = 1069) aged 18-87 years, completed a questionnaire measuring their intentions to engage in binge drinking and frequent drinking. As research indicates that drinking trends are a function of age, hierarchical multiple regressions were conducted separately for four age groups (18-24, 25-34, 35-44, 45, and above). Results supported the predictive utility of the TPB, (particularly Attitudes and Perceived Behavioral Control). Across the age groups, the final models explained between 48% and 62% of the variance in intentions to binge drink and between 33% and 51% of the variance in intentions to drink frequently. Subjective norms were significant associated with the youngest group (18-24 years) and the oldest group (45+ years). Self-identity was significantly associated with intentions to binge drink in younger women. Implications are discussed with regard to the predictive utility of an extended TPB to include self-identity in determining women's intentions to consume alcohol. Key factors that influence women's decisions to engage in risky drinking behaviors have been underlined to inform future interventions.

Predictors of non- hookah smoking among high-school students based on prototype/willingness model.

PubMed

Abedini, Sedigheh; MorowatiSharifabad, MohammadAli; Chaleshgar Kordasiabi, Mosharafeh; Ghanbarnejad, Amin

2014-01-01

The aim of the study was to determine predictors of refraining from hookah smoking among high-school students in Bandar Abbas, southern Iran based on Prototype/Willingness model. This cross- sectional with analytic approach was performed on 240 high-school students selected by a cluster random sampling. The data of demographic and Prototype-Willingness Model constructs were acquired via a self-administrated questionnaire. Data were analyzed by mean, frequency, correlation, liner and logistic regression statistical tests. Statistically significant determinants of the intention to refrain from hookah smoking were subjective norms, willingness, and attitude. Regression model indicated that the three items together explained 46.9% of the non-smoking hookah intention variance. Attitude and subjective norms predicted 36.0% of the non-smoking hookah intention variance. There was a significant relationship between the participants' negative prototype about the hookah smokers and the willingness to avoid from hookah smoking (P=0.002). Also willingness predicted non-smoking hookah better than the intention (P<0.001). Deigning intervention to increase negative prototype about the hookah smokers and reducing situations and conditions which facilitate hookah smoking, such as easy access to tobacco products in the cafés, beaches can be useful results among adolescents to hookah smoking prevention.

Predictors of self-rated health in patients with chronic nonmalignant pain.

PubMed

Siedlecki, Sandra L

2006-09-01

Self-rated health (SRH) is an important outcome measure that has been found to accurately predict mortality, morbidity, function, and psychologic well-being. Chronic nonmalignant pain presents with a pattern that includes low levels of power and high levels of pain, depression, and disability. Differences in SRH may be related to variations within this pattern. The purpose of this analysis was to identify determinants of SRH and test their ability to predict SRH in patients with chronic nonmalignant pain. SRH was measured by response to a single three-option age-comparative question. The Power as Knowing Participation in Change Tool, McGill Pain Questionnaire Short Form, Center for Epidemiological Studies Depression Scale, and Pain Disability Index were used to measure independent variables. Multivariate analysis of variance revealed significant differences (p = .001) between SRH categories on the combined dependent variable. Analysis of variance conducted as a follow-up identified significant differences for power (p < .001) and depression (p = .003), but not for pain or pain-related disability; and discriminant analysis found that power and depression correctly classified patients with 75% accuracy. Findings suggest pain interventions designed to improve mood and provide opportunities for knowing participation may have a greater impact on overall health than those that target only pain and disability.

Mothers of children with externalizing behavior problems: cognitive risk factors for abuse potential and discipline style and practices.

PubMed

McElroy, Erika M; Rodriguez, Christina M

2008-08-01

Utilizing the conceptual framework of the Social Information Processing (SIP) model (Milner, 1993, 2000), associations between cognitive risk factors and child physical abuse risk and maladaptive discipline style and practices were examined in an at-risk population. Seventy-three mothers of 5-12-year-old children, who were identified by their therapist as having an externalizing behavior problem, responded to self-report measures pertaining to cognitive risk factors (empathic perspective taking, frustration tolerance, developmental expectations, parenting locus of control), abuse risk, and discipline style and practices. The Child Behavior Checklist (CBCL) provided a confirmation of the child's externalizing behaviors independent of the therapist's assessment. The results of this study suggest several cognitive risk factors significantly predict risk of parental aggression toward children. A parent's ability to empathize and take the perspective of their child, parental locus of control, and parental level of frustration tolerance were significant predictors of abuse potential (accounting for 63% of the variance) and inappropriate discipline practices (accounting for 55% of the variance). Findings of the present study provide support for processes theorized in the SIP model. Specifically, results underscore the potential role of parents' frustration tolerance, developmental expectations, locus of control, and empathy as predictive of abuse potential and disciplinary style in an at-risk sample.

Validity of the Test of Infant Motor Performance for prediction of 6-, 9- and 12-month scores on the Alberta Infant Motor Scale.

PubMed

Campbell, Suzann K; Kolobe, Thubi H A; Wright, Benjamin D; Linacre, John Michael

2002-04-01

The Test of Infant Motor Performance (TIMP) is a test of functional movement in infants from 32 weeks' post-conceptional age to 4 months postterm. The purpose of this study was to assess in 96 infants (44 females, 52 males) with varying risk, the relation between measures on the TIMP at 7, 30, 60, and 90 days after term age and percentile ranks (PR) on the Alberta Infant Motor Scale (AIMS). Correlation between scores on the TIMP and the AIMS was highest for TIMP tests at 90 days and AIMS testing at 6 months (r=0.67, p=0.0001), but all comparisons were statistically significant except those between the TIMP at 7 days and AIMS PR at 9 months. In a multiple regression analysis combining a perinatal risk score and 7-day TIMP measures to predict 12-month AIMS PR, risk, but not TIMP, predicted outcome (21% of variance explained). At older ages TIMP measures made increasing contributions to prediction of 12-month AIMS PR (30% of variance explained by 90-day TIMP). The best TIMP score to maximize specificity and correctly identify 84% of the infants above versus below the 10th PR at 6 months was a cut-off point of 1 SD below the mean. The same cut-off point correctly identified 88% of the infants at 12 months. A cut-off of -0.5 SD, however, maximized sensitivity at 92%. A negative test result, i.e. score above -0.5 SD at 3 months, carried only a 2% probability of a poor 12-month outcome. We conclude that TIMP scores significantly predict AIMS PR 6 to 12 months later, but the TIMP at 3 months of age has the greatest degree of validity for predicting motor performance on the AIMS at 12 months and can be used clinically to identify infants likely to benefit from intervention.

Core self-evaluation as a predictor of strength training adoption in older adults.

PubMed

Baker, Michael K; Kennedy, David J; Bohle, Philip L; Campbell, Deena; Wiltshire, James H; Singh, Maria A Fiatarone

2011-01-01

Progressive resistance training (PRT) counteracts sarcopenia and has been demonstrated to improve physical function and quality of life in older adults. Despite the clear benefits of PRT, participation remains low. The core self-evaluation (CSE) construct is theoretically antecedent to four personality traits: locus of control, self-esteem, neuroticism (emotional stability), and generalized self-efficacy. We have examined the association of CSE with exercise adoption among older adults invited to participate in a PRT trial. We hypothesized that CSE would positively predict adoption of PRT. All residents of two retirement communities were invited to complete questionnaires with items on demographics, physical activity, CSE, and general health. Following completion of questionnaires, residents were invited to take part in an on-site, 10-week randomized controlled trial of a PRT-based exercise trial. Thirty-eight of 358 residents (63.2% women; 76.6±6.1 year; range 58-92) enrolled and 118 residents completed the questionnaires. Multiple regression analysis predicting PRT adoption indicated that the demographic variables accounted for 38% of the variance. Inclusion of CSE (β=.405) accounted for an additional 10% of the variance in PRT adoption. CSE was predictive of PRT adoption in this cohort, adding significantly to the predictive efficacy of known demographic predictors. This is the first study to show that CSE may influence adoption of PRT in any cohort. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Sequential causal inference: Application to randomized trials of adaptive treatment strategies

PubMed Central

Dawson, Ree; Lavori, Philip W.

2009-01-01

SUMMARY Clinical trials that randomize subjects to decision algorithms, which adapt treatments over time according to individual response, have gained considerable interest as investigators seek designs that directly inform clinical decision making. We consider designs in which subjects are randomized sequentially at decision points, among adaptive treatment options under evaluation. We present a sequential method to estimate the comparative effects of the randomized adaptive treatments, which are formalized as adaptive treatment strategies. Our causal estimators are derived using Bayesian predictive inference. We use analytical and empirical calculations to compare the predictive estimators to (i) the ‘standard’ approach that allocates the sequentially obtained data to separate strategy-specific groups as would arise from randomizing subjects at baseline; (ii) the semi-parametric approach of marginal mean models that, under appropriate experimental conditions, provides the same sequential estimator of causal differences as the proposed approach. Simulation studies demonstrate that sequential causal inference offers substantial efficiency gains over the standard approach to comparing treatments, because the predictive estimators can take advantage of the monotone structure of shared data among adaptive strategies. We further demonstrate that the semi-parametric asymptotic variances, which are marginal ‘one-step’ estimators, may exhibit significant bias, in contrast to the predictive variances. We show that the conditions under which the sequential method is attractive relative to the other two approaches are those most likely to occur in real studies. PMID:17914714

The Cohesive Population Genetics of Molecular Drive

PubMed Central

Ohta, Tomoko; Dover, Gabriel A.

1984-01-01

The long-term population genetics of multigene families is influenced by several biased and unbiased mechanisms of nonreciprocal exchanges (gene conversion, unequal exchanges, transposition) between member genes, often distributed on several chromosomes. These mechanisms cause fluctuations in the copy number of variant genes in an individual and lead to a gradual replacement of an original family of n genes (A) in N number of individuals by a variant gene (a). The process for spreading a variant gene through a family and through a population is called molecular drive. Consideration of the known slow rates of nonreciprocal exchanges predicts that the population variance in the copy number of gene a per individual is small at any given generation during molecular drive. Genotypes at a given generation are expected only to range over a small section of all possible genotypes from one extreme (n number of A) to the other (n number of a). A theory is developed for estimating the size of the population variance by using the concept of identity coefficients. In particular, the variance in the course of spreading of a single mutant gene of a multigene family was investigated in detail, and the theory of identity coefficients at the state of steady decay of genetic variability proved to be useful. Monte Carlo simulations and numerical analysis based on realistic rates of exchange in families of known size reveal the correctness of the theoretical prediction and also assess the effect of bias in turnover. The population dynamics of molecular drive in gradually increasing the mean copy number of a variant gene without the generation of a large variance (population cohesion) is of significance regarding potential interactions between natural selection and molecular drive. PMID:6500260

The cohesive population genetics of molecular drive.

PubMed

Ohta, T; Dover, G A

1984-10-01

The long-term population genetics of multigene families is influenced by several biased and unbiased mechanisms of nonreciprocal exchanges (gene conversion, unequal exchanges, transposition) between member genes, often distributed on several chromosomes. These mechanisms cause fluctuations in the copy number of variant genes in an individual and lead to a gradual replacement of an original family of n genes (A) in N number of individuals by a variant gene (a). The process for spreading a variant gene through a family and through a population is called molecular drive. Consideration of the known slow rates of nonreciprocal exchanges predicts that the population variance in the copy number of gene a per individual is small at any given generation during molecular drive. Genotypes at a given generation are expected only to range over a small section of all possible genotypes from one extreme (n number of A) to the other (n number of a). A theory is developed for estimating the size of the population variance by using the concept of identity coefficients. In particular, the variance in the course of spreading of a single mutant gene of a multigene family was investigated in detail, and the theory of identity coefficients at the state of steady decay of genetic variability proved to be useful. Monte Carlo simulations and numerical analysis based on realistic rates of exchange in families of known size reveal the correctness of the theoretical prediction and also assess the effect of bias in turnover. The population dynamics of molecular drive in gradually increasing the mean copy number of a variant gene without the generation of a large variance (population cohesion) is of significance regarding potential interactions between natural selection and molecular drive.

Variance computations for functional of absolute risk estimates.

PubMed

Pfeiffer, R M; Petracci, E

2011-07-01

We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.

Variance computations for functional of absolute risk estimates

PubMed Central

Pfeiffer, R.M.; Petracci, E.

2011-01-01

We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates. PMID:21643476

Maternal Factors Predicting Cognitive and Behavioral Characteristics of Children with Fetal Alcohol Spectrum Disorders

PubMed Central

May, Philip A.; Tabachnick, Barbara G.; Gossage, J. Phillip; Kalberg, Wendy O.; Marais, Anna-Susan; Robinson, Luther K.; Manning, Melanie A.; Blankenship, Jason; Buckley, David; Hoyme, H. Eugene; Adnams, Colleen M.

2013-01-01

Objective To provide an analysis of multiple predictors of cognitive and behavioral traits for children with fetal alcohol spectrum disorders (FASD). Method Multivariate correlation techniques were employed with maternal and child data from epidemiologic studies in a community in South Africa. Data on 561 first grade children with fetal alcohol syndrome (FAS), partial FAS (PFAS), and not FASD and their mothers were analyzed by grouping 19 maternal variables into categories (physical, demographic, childbearing, and drinking) and employed in structural equation models (SEM) to assess correlates of child intelligence (verbal and non-verbal) and behavior. Results A first SEM utilizing only seven maternal alcohol use variables to predict cognitive/behavioral traits was statistically significant (B = 3.10, p < .05), but explained only 17.3% of the variance. The second model incorporated multiple maternal variables and was statistically significant explaining 55.3% of the variance. Significantly correlated with low intelligence and problem behavior were demographic (B = 3.83, p < .05) (low maternal education, low socioeconomic status (SES), and rural residence) and maternal physical characteristics (B = 2.70, p < .05) (short stature, small head circumference, and low weight). Childbearing history and alcohol use composites were not statistically significant in the final complex model, and were overpowered by SES and maternal physical traits. Conclusions While other analytic techniques have amply demonstrated the negative effects of maternal drinking on intelligence and behavior, this highly-controlled analysis of multiple maternal influences reveals that maternal demographics and physical traits make a significant enabling or disabling contribution to child functioning in FASD. PMID:23751886

Sources of genetic and phenotypic variance in fertilization rates and larval traits in a sea urchin.

PubMed

Evans, Jonathan P; García-González, Francisco; Marshall, Dustin J

2007-12-01

In nonresource based mating systems females are thought to derive indirect genetic benefits by mating with high-quality males. Such benefits can be due either to the intrinsic genetic quality of sires or to beneficial interactions between maternal and paternal haplotypes. Animals with external fertilization and no parental care offer unrivaled opportunities to address these hypotheses. With these systems, cross-classified breeding designs and in vitro fertilization can be used to disentangle sources of genetic and environmental variance in offspring fitness. Here, we employ these approaches in the Australian sea urchin Heliocidaris erythrogramma and explore how sire-dam identities influence fertilization rates, embryo viability (survival to hatching), and metamorphosis, as well as the interrelationships between these potential fitness traits. We show that fertilization is influenced by a combination of strong maternal effects and intrinsic male effects. Our subsequent analysis of embryo viability, however, revealed a highly significant interaction between parental genotypes, indicating that partial incompatibilities can severely limit offspring survival at this life-history stage. Importantly, we detected no significant relationship between fertilization rates and embryo viability. This finding suggests that fertilization rates should not be inferred from hatching rates, which is commonly practiced in species in which it is not possible to estimate fertilization at conception. Finally, we detected significant additive genetic variance due to sires in rates of juvenile metamorphosis, and a positive correlation between fertilization rates and metamorphosis. This latter finding indicates that the performance of a male's ejaculate in noncompetitive IVF trials predicts heritable offspring traits, although the fitness implications of variance in rates of spontaneous juvenile metamorphosis have yet to be determined.

Evaluating emotional sensitivity and tolerance factors in the prediction of panic-relevant responding to a biological challenge.

PubMed

Kutz, Amanda; Marshall, Erin; Bernstein, Amit; Zvolensky, Michael J

2010-01-01

The current study investigated anxiety sensitivity, distress tolerance (Simons & Gaher, 2005), and discomfort intolerance (Schmidt, Richey, Cromer, & Buckner, 2007) in relation to panic-relevant responding (i.e., panic attack symptoms and panic-relevant cognitions) to a 10% carbon dioxide enriched air challenge. Participants were 216 adults (52.6% female; M(age)=22.4, SD=9.0). A series of hierarchical multiple regressions was conducted with covariates of negative affectivity and past year panic attack history in step one of the model, and anxiety sensitivity, discomfort intolerance, and distress tolerance entered simultaneously into step two. Results indicated that anxiety sensitivity, but not distress tolerance or discomfort intolerance, was significantly incrementally predictive of physical panic attack symptoms and cognitive panic attack symptoms. Additionally, anxiety sensitivity was significantly predictive of variance in panic attack status during the challenge. These findings emphasize the important, unique role of anxiety sensitivity in predicting risk for panic psychopathology, even when considered in the context of other theoretically relevant emotion vulnerability variables.

Examining Predictive Validity of Oral Reading Fluency Slope in Upper Elementary Grades Using Quantile Regression.

PubMed

Cho, Eunsoo; Capin, Philip; Roberts, Greg; Vaughn, Sharon

2017-07-01

Within multitiered instructional delivery models, progress monitoring is a key mechanism for determining whether a child demonstrates an adequate response to instruction. One measure commonly used to monitor the reading progress of students is oral reading fluency (ORF). This study examined the extent to which ORF slope predicts reading comprehension outcomes for fifth-grade struggling readers ( n = 102) participating in an intensive reading intervention. Quantile regression models showed that ORF slope significantly predicted performance on a sentence-level fluency and comprehension assessment, regardless of the students' reading skills, controlling for initial ORF performance. However, ORF slope was differentially predictive of a passage-level comprehension assessment based on students' reading skills when controlling for initial ORF status. Results showed that ORF explained unique variance for struggling readers whose posttest performance was at the upper quantiles at the end of the reading intervention, but slope was not a significant predictor of passage-level comprehension for students whose reading problems were the most difficult to remediate.

Leg pain and psychological variables predict outcome 2-3 years after lumbar fusion surgery.

PubMed

Abbott, Allan D; Tyni-Lenné, Raija; Hedlund, Rune

2011-10-01

Prediction studies testing a thorough range of psychological variables in addition to demographic, work-related and clinical variables are lacking in lumbar fusion surgery research. This prospective cohort study aimed at examining predictions of functional disability, back pain and health-related quality of life (HRQOL) 2-3 years after lumbar fusion by regressing nonlinear relations in a multivariate predictive model of pre-surgical variables. Before and 2-3 years after lumbar fusion surgery, patients completed measures investigating demographics, work-related variables, clinical variables, functional self-efficacy, outcome expectancy, fear of movement/(re)injury, mental health and pain coping. Categorical regression with optimal scaling transformation, elastic net regularization and bootstrapping were used to investigate predictor variables and address predictive model validity. The most parsimonious and stable subset of pre-surgical predictor variables explained 41.6, 36.0 and 25.6% of the variance in functional disability, back pain intensity and HRQOL 2-3 years after lumbar fusion. Pre-surgical control over pain significantly predicted functional disability and HRQOL. Pre-surgical catastrophizing and leg pain intensity significantly predicted functional disability and back pain while the pre-surgical straight leg raise significantly predicted back pain. Post-operative psychomotor therapy also significantly predicted functional disability while pre-surgical outcome expectations significantly predicted HRQOL. For the median dichotomised classification of functional disability, back pain intensity and HRQOL levels 2-3 years post-surgery, the discriminative ability of the prediction models was of good quality. The results demonstrate the importance of pre-surgical psychological factors, leg pain intensity, straight leg raise and post-operative psychomotor therapy in the predictions of functional disability, back pain and HRQOL-related outcomes.

Predicting self-care behaviours of patients with type 2 diabetes: the importance of beliefs about behaviour, not just beliefs about illness.

PubMed

French, David P; Wade, Alisha N; Farmer, Andrew J

2013-04-01

There is evidence that perceptions of treatment may be more predictive than illness perceptions, e.g. medication adherence is often better predicted by beliefs about medication than by beliefs about illness. The present study aims to assess the generality of this finding, by comparing the extent to which self-care behaviours of patients with type 2 diabetes are predicted by patients' beliefs about those behaviours, compared with their illness perceptions. This study is a one year prospective cohort analysis of 453 patients recruited to a randomised trial of blood glucose self-monitoring. Behaviour was assessed by the medication adherence report scale (MARS) and diabetes self-care activities (DSCA) scales; illness perceptions by IPQ-R; study-specific scales of beliefs about diet and physical activity were constructed by factor analysing items based on beliefs elicited in an earlier interview study involving patients with type 2 diabetes. Past behaviour, trial group allocation, and clinical and demographic factors predicted between 16% and 35% variance in medication adherence, exercise, and diet scales. Illness perceptions added between 0.9% and 4.5% additional variance; beliefs about behaviour added a further 1.1% to 6.4% additional variance. Beliefs regarding, respectively, the importance of exercise in controlling diabetes, the need to east less, and enjoyment from eating sweet or fatty food, added unique variance. Beliefs about behaviour are at least as important as beliefs about illness in predicting several health-related behaviours. This suggests the possibility that behaviour change interventions with patient groups would be more effective by targeting beliefs about behaviour, rather than beliefs about illness. Copyright © 2012 Elsevier Inc. All rights reserved.

Genome-Enabled Estimates of Additive and Nonadditive Genetic Variances and Prediction of Apple Phenotypes Across Environments

PubMed Central

Kumar, Satish; Molloy, Claire; Muñoz, Patricio; Daetwyler, Hans; Chagné, David; Volz, Richard

2015-01-01

The nonadditive genetic effects may have an important contribution to total genetic variation of phenotypes, so estimates of both the additive and nonadditive effects are desirable for breeding and selection purposes. Our main objectives were to: estimate additive, dominance and epistatic variances of apple (Malus × domestica Borkh.) phenotypes using relationship matrices constructed from genome-wide dense single nucleotide polymorphism (SNP) markers; and compare the accuracy of genomic predictions using genomic best linear unbiased prediction models with or without including nonadditive genetic effects. A set of 247 clonally replicated individuals was assessed for six fruit quality traits at two sites, and also genotyped using an Illumina 8K SNP array. Across several fruit quality traits, the additive, dominance, and epistatic effects contributed about 30%, 16%, and 19%, respectively, to the total phenotypic variance. Models ignoring nonadditive components yielded upwardly biased estimates of additive variance (heritability) for all traits in this study. The accuracy of genomic predicted genetic values (GEGV) varied from about 0.15 to 0.35 for various traits, and these were almost identical for models with or without including nonadditive effects. However, models including nonadditive genetic effects further reduced the bias of GEGV. Between-site genotypic correlations were high (>0.85) for all traits, and genotype-site interaction accounted for <10% of the phenotypic variability. The accuracy of prediction, when the validation set was present only at one site, was generally similar for both sites, and varied from about 0.50 to 0.85. The prediction accuracies were strongly influenced by trait heritability, and genetic relatedness between the training and validation families. PMID:26497141

Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials.

PubMed

Cuevas, Jaime; Granato, Italo; Fritsche-Neto, Roberto; Montesinos-Lopez, Osval A; Burgueño, Juan; Bandeira E Sousa, Massaine; Crossa, José

2018-03-28

In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multi-environment environment-specific variance G×E deviation model (MDe) where the random genetic effects of the lines are modeled with the markers (or pedigree). With the objective of further modeling the genetic residual of the lines, we incorporated the random intercepts of the lines ([Formula: see text]) and generated another three models. Each of these 6 models were fitted with a linear kernel method (Genomic Best Linear Unbiased Predictor, GB) and a Gaussian Kernel (GK) method. We compared these 12 model-method combinations with another two multi-environment G×E interactions models with unstructured variance-covariances (MUC) using GB and GK kernels (4 model-method). Thus, we compared the genomic-enabled prediction accuracy of a total of 16 model-method combinations on two maize data sets with positive phenotypic correlations among environments, and on two wheat data sets with complex G×E that includes some negative and close to zero phenotypic correlations among environments. The two models (MDs and MDE with the random intercept of the lines and the GK method) were computationally efficient and gave high prediction accuracy in the two maize data sets. Regarding the more complex G×E wheat data sets, the prediction accuracy of the model-method combination with G×E, MDs and MDe, including the random intercepts of the lines with GK method had important savings in computing time as compared with the G×E interaction multi-environment models with unstructured variance-covariances but with lower genomic prediction accuracy. Copyright © 2018 Cuevas et al.

Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials

PubMed Central

Cuevas, Jaime; Granato, Italo; Fritsche-Neto, Roberto; Montesinos-Lopez, Osval A.; Burgueño, Juan; Bandeira e Sousa, Massaine; Crossa, José

2018-01-01

In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multi-environment environment-specific variance G×E deviation model (MDe) where the random genetic effects of the lines are modeled with the markers (or pedigree). With the objective of further modeling the genetic residual of the lines, we incorporated the random intercepts of the lines (l) and generated another three models. Each of these 6 models were fitted with a linear kernel method (Genomic Best Linear Unbiased Predictor, GB) and a Gaussian Kernel (GK) method. We compared these 12 model-method combinations with another two multi-environment G×E interactions models with unstructured variance-covariances (MUC) using GB and GK kernels (4 model-method). Thus, we compared the genomic-enabled prediction accuracy of a total of 16 model-method combinations on two maize data sets with positive phenotypic correlations among environments, and on two wheat data sets with complex G×E that includes some negative and close to zero phenotypic correlations among environments. The two models (MDs and MDE with the random intercept of the lines and the GK method) were computationally efficient and gave high prediction accuracy in the two maize data sets. Regarding the more complex G×E wheat data sets, the prediction accuracy of the model-method combination with G×E, MDs and MDe, including the random intercepts of the lines with GK method had important savings in computing time as compared with the G×E interaction multi-environment models with unstructured variance-covariances but with lower genomic prediction accuracy. PMID:29476023

Skill and predictability in multimodel ensemble forecasts for Northern Hemisphere regions with dominant winter precipitation

NASA Astrophysics Data System (ADS)

Ehsan, Muhammad Azhar; Tippett, Michael K.; Almazroui, Mansour; Ismail, Muhammad; Yousef, Ahmed; Kucharski, Fred; Omar, Mohamed; Hussein, Mahmoud; Alkhalaf, Abdulrahman A.

2017-05-01

Northern Hemisphere winter precipitation reforecasts from the European Centre for Medium Range Weather Forecast System-4 and six of the models in the North American Multi-Model Ensemble are evaluated, focusing on two regions (Region-A: 20°N-45°N, 10°E-65°E and Region-B: 20°N-55°N, 205°E-255°E) where winter precipitation is a dominant fraction of the annual total and where precipitation from mid-latitude storms is important. Predictability and skill (deterministic and probabilistic) are assessed for 1983-2013 by the multimodel composite (MME) of seven prediction models. The MME climatological mean and variability over the two regions is comparable to observation with some regional differences. The statistically significant decreasing trend observed in Region-B precipitation is captured well by the MME and most of the individual models. El Niño Southern Oscillation is a source of forecast skill, and the correlation coefficient between the Niño3.4 index and precipitation over region A and B is 0.46 and 0.35, statistically significant at the 95 % level. The MME reforecasts weakly reproduce the observed teleconnection. Signal, noise and signal to noise ratio analysis show that the signal variance over two regions is very small as compared to noise variance which tends to reduce the prediction skill. The MME ranked probability skill score is higher than that of individual models, showing the advantage of a multimodel ensemble. Observed Region-A rainfall anomalies are strongly associated with the North Atlantic Oscillation, but none of the models reproduce this relation, which may explain the low skill over Region-A. The superior quality of multimodel ensemble compared with individual models is mainly due to larger ensemble size.

Overgeneral autobiographical memory in patients with chronic pain.

PubMed

Liu, Xianhua; Liu, Yanling; Li, Li; Hu, Yiqiu; Wu, Siwei; Yao, Shuqiao

2014-03-01

Overgenerality and delay of the retrieval of autobiographical memory (AM) are well documented in a range of clinical conditions, particularly in patients with emotional disorder. The present study extended the investigation to chronic pain, attempting to identify whether the retrieval of AM in patients with chronic pain tends to be overgeneral or delayed. With an observational cross-sectional design, we evaluated the AM both in patients with chronic pain and healthy controls by Autobiographical Memory Test. Pain conditions were assessed using the pain diagnostic protocol, the short-form McGill Pain Questionnaire (SF-MPQ), and the Pain Self-Efficacy Questionnaire (PSEQ). Emotion was assessed using the Beck Depression Inventory-II (BDI-II) and the Beck Anxiety Inventory. Subjects included 176 outpatients with chronic pain lasting for at least 6 months and 170 healthy controls. 1) Compared with the healthy group, the chronic pain group had more overgeneral memories (OGMs) (F = 29.061, P < 0.01) and longer latency (F = 13.602, P < 0.01). 2) In the chronic pain group, the stepwise multiple regression models for variables predicting OGM were significant (P < 0.01). Specifically, the variance in OGM scores could be predicted by the BDI score (9.7%), pain chronicity (4.3%), PSEQ score (7.1%), and Affective Index (of SF-MPQ) score (2.7%). 3) In the chronic pain group, the stepwise multiple regression models for variables predicting latency were significant (P < 0.05). Specifically, the variance in latency could be predicted by age (3.1%), pain chronicity (2.7%), pain duration (4.3%), and PSEQ score (2.0%). The retrieval of AM in patients with chronic pain tends to be overgeneral and delayed, and the retrieval style of AM may be contributed to negative emotions and chronic pain conditions. Wiley Periodicals, Inc.

Using the Positive and Negative Syndrome Scale (PANSS) to Define Different Domains of Negative Symptoms

PubMed Central

Khan, Anzalee; Keefe, Richard S. E.

2017-01-01

Background: Reduced emotional experience and expression are two domains of negative symptoms. The authors assessed these two domains of negative symptoms using previously developed Positive and Negative Syndrome Scale (PANSS) factors. Using an existing dataset, the authors predicted three different elements of everyday functioning (social, vocational, and everyday activities) with these two factors, as well as with performance on measures of functional capacity. Methods: A large (n=630) sample of people with schizophrenia was used as the data source of this study. Using regression analyses, the authors predicted the three different aspects of everyday functioning, first with just the two Positive and Negative Syndrome Scale factors and then with a global negative symptom factor. Finally, we added neurocognitive performance and functional capacity as predictors. Results: The Positive and Negative Syndrome Scale reduced emotional experience factor accounted for 21 percent of the variance in everyday social functioning, while reduced emotional expression accounted for no variance. The total Positive and Negative Syndrome Scale negative symptom factor accounted for less variance (19%) than the reduced experience factor alone. The Positive and Negative Syndrome Scale expression factor accounted for, at most, one percent of the variance in any of the functional outcomes, with or without the addition of other predictors. Implications: Reduced emotional experience measured with the Positive and Negative Syndrome Scale, often referred to as “avolition and anhedonia,” specifically predicted impairments in social outcomes. Further, reduced experience predicted social impairments better than emotional expression or the total Positive and Negative Syndrome Scale negative symptom factor. In this cross-sectional study, reduced emotional experience was specifically related with social outcomes, accounting for essentially no variance in work or everyday activities, and being the sole meaningful predictor of impairment in social outcomes. PMID:29410933

Quantifying predictability variations in a low-order ocean-atmosphere model - A dynamical systems approach

NASA Technical Reports Server (NTRS)

Nese, Jon M.; Dutton, John A.

1993-01-01

The predictability of the weather and climatic states of a low-order moist general circulation model is quantified using a dynamic systems approach, and the effect of incorporating a simple oceanic circulation on predictability is evaluated. The predictability and the structure of the model attractors are compared using Liapunov exponents, local divergence rates, and the correlation and Liapunov dimensions. It was found that the activation of oceanic circulation increases the average error doubling time of the atmosphere and the coupled ocean-atmosphere system by 10 percent and decreases the variance of the largest local divergence rate by 20 percent. When an oceanic circulation develops, the average predictability of annually averaged states is improved by 25 percent and the variance of the largest local divergence rate decreases by 25 percent.

Predicting self-construal from authoritarianism: a pilot study of perceived threat.

PubMed

Shaffer, Barbara A; Hollen, Ryan D; Hastings, Brad M

2007-12-01

This pilot study investigated the association of perceived threat and scores on a measure of Authoritarianism. Undergraduate students (29 women, 8 men; ages 18-32, M=21, SD=3.1), completed the Right-wing Authoritarianism scale and then the Self-construal scale after reading a nonthreatening or threatening news article. In the threatening condition, Authoritarian scores accounted for a significant amount of variance (R2= .26) in Interdependent Self-construal scores, but not for Independent Self-construal scores. No significant associations were found in the non-threatening condition.

The role of maladaptive appraisals in child acute stress reactions.

PubMed

Salmon, Karen; Sinclair, Emma; Bryant, Richard A

2007-06-01

To test the prediction of cognitive models of trauma that negative, catastrophic appraisals central to the development of psychopathological stress reactions. A cross-sectional, concurrent design was used. Sixty-six children (aged 7-13 years), who were hospitalized after traumatic injury were assessed within 4 weeks of their trauma for acute stress disorder, depression, and administered the Child Post-traumatic Cognitions Inventory (cPTCI). Parental acute stress was also assessed. Children's negative appraisals of their ongoing vulnerability accounted for 44% of the variance of acute stress reactions in children. Injury severity, depression, age, and parental acute stress levels did not account for significant additional variance. The findings provide support for cognitive models of trauma adaptation and highlight the importance of assessing children's appraisals of their traumatic experience in order to develop effective interventions.

Toddler Emotional States, Temperamental Traits, and Their Interaction: Associations with Mothers’ and Fathers’ Parenting

PubMed Central

Fields, Margaret A.; Cole, Pamela M.; Maggi, Mirella C.

2016-01-01

We investigated the degree to which toddlers’ observed emotional states, toddlers’ temperamental traits, and their interaction accounted for variance in mothers’ and fathers’ parenting. Main effects of two emotional states (positive emotion and negative emotion), three temperamental traits (negative affectivity, effortful control, and surgency) as well as state-by-trait interactions, were examined in relation to parental sensitivity, positive affect, and negative affect. The hypothesis that toddlers’ temperamental traits would moderate the association between their observed emotional states and parenting was partially supported. Significant state-by-trait interactions were found in models predicting the probability that mothers and fathers expressed negative affect towards their toddlers. For parental sensitivity and positive affect, only main effects of temperament and/or emotion expression accounted for variance in parenting. PMID:28479643

Predictors of posttraumatic stress symptoms following childbirth

PubMed Central

2014-01-01

Background Posttraumatic stress disorder (PTSD) following childbirth has gained growing attention in the recent years. Although a number of predictors for PTSD following childbirth have been identified (e.g., history of sexual trauma, emergency caesarean section, low social support), only very few studies have tested predictors derived from current theoretical models of the disorder. This study first aimed to replicate the association of PTSD symptoms after childbirth with predictors identified in earlier research. Second, cognitive predictors derived from Ehlers and Clark’s (2000) model of PTSD were examined. Methods N = 224 women who had recently given birth completed an online survey. In addition to computing single correlations between PTSD symptom severities and variables of interest, in a hierarchical multiple regression analyses posttraumatic stress symptoms were predicted by (1) prenatal variables, (2) birth-related variables, (3) postnatal social support, and (4) cognitive variables. Results Wellbeing during pregnancy and age were the only prenatal variables contributing significantly to the explanation of PTSD symptoms in the first step of the regression analysis. In the second step, the birth-related variables peritraumatic emotions and wellbeing during childbed significantly increased the explanation of variance. Despite showing significant bivariate correlations, social support entered in the third step did not predict PTSD symptom severities over and above the variables included in the first two steps. However, with the exception of peritraumatic dissociation all cognitive variables emerged as powerful predictors and increased the amount of variance explained from 43% to a total amount of 68%. Conclusions The findings suggest that the prediction of PTSD following childbirth can be improved by focusing on variables derived from a current theoretical model of the disorder. PMID:25026966

The relations among upper-extremity loading characteristics and bone mineral density changes in young women.

PubMed

Wang, Man-Ying; Salem, George J

2004-06-01

The relations among the reaction forces engendered during an upper-extremity dynamic impact-loading exercise (DILE) program and bone mineral density adaptations (DeltaBMD) in the radius were investigated in 24 healthy premenopausal women (mean age = 29 +/- 6 years). Subjects performed DILE 36 cycles/day, 3 days/week for 24 weeks. The exercised arm was allocated randomly to either the dominant or the nondominant limb. In addition, subjects were assigned randomly into either damped or nondamped treatment arms to examine the effects of both higher- and lower-magnitude loading prescriptions. Measurements including anthropometrics, self-reported physical activity levels, hand-grip strength, radial BMD (DEXA, Hologic QDR1500, MA) at the ultradistal radius (UD), distal 1/3 radius (DR), and total distal radius (TOTAL), and exercise-related loading characteristics (impact load, loading rate, and impulse) were recorded at baseline and at 6 months. Simple linear regression models were used to fit the regional BMD changes to the reaction force, changes in hand-grip strength (DeltaGRIP), and changes in body weight (DeltaBW). Findings demonstrated that the damping condition utilized during DILE influenced the relations between loading events and BMD changes. Specifically, none of the reaction-force characteristics significantly predicted changes in BMD in participants performing DILE using the damped condition, whereas, in the nondamped condition, impact load accounted for 58% of the variance in BMD change at DR and 66% of the variance in BMD change at TOTAL. Thresholds of 345 and 285 N of impact force to promote BMD increases at DR and TOTAL, respectively, were obtained from the regression models in the nondamped group. Impulse was also an independent predictor of BMD changes at TOTAL, accounting for 56% of the variance. Neither DeltaGRIP nor DeltaBW significantly predicted DeltaBMD at any radial site. These findings, in young adult women, parallel previous reports identifying significant, regionally specific relations among external loading events and BMD changes in both animal and human models.

The role of intolerance of uncertainty in terms of alcohol use motives among college students.

PubMed

Kraemer, Kristen M; McLeish, Alison C; O'Bryan, Emily M

2015-03-01

Hazardous drinking rates among college students are exceedingly high. Despite the link between worry and alcohol use problems, there has been a dearth of empirical work examining worry-related risk factors in terms of motivations for alcohol use. Therefore, the aim of the present investigation was to examine the unique predictive ability of intolerance of uncertainty in terms of alcohol use motives. Participants were 389 college students (72.2% female, Mage=19.92, SD=3.87, Range=18-58 years) who completed self-report measures for course credit. As hypothesized, after controlling for the effects of gender, smoking status, marijuana use status, alcohol consumption, negative affect, and anxiety sensitivity, greater levels of intolerance of uncertainty were significantly predictive of greater coping (1.5% unique variance) and conformity (4.7% unique variance) drinking motives, but not social or enhancement drinking motives. These results suggest that intolerance of uncertainty is associated with drinking to manage or avoid negative emotions, and interventions aimed at reducing intolerance of uncertainty may be helpful in reducing problematic alcohol consumption among college students. Copyright © 2014 Elsevier Ltd. All rights reserved.

Bullying among Spanish secondary education students: the role of gender traits, sexism, and homophobia.

PubMed

Carrera-Fernández, María-Victoria; Lameiras-Fernández, María; Rodríguez-Castro, Yolanda; Vallejo-Medina, Pablo

2013-09-01

The aim of the present study was to assess the combined influence of gender stereotypes, sexism, and homophobia on attitudes toward bullying and bullying behavior. A total of 1,500 Spanish adolescents between 12 and 18 years of age (49.3% girls and 50.7% boys) completed a questionnaire that included measures of bullying, attitudes toward bullying, gender-stereotyped personality traits (instrumentality and expressiveness), hostile and benevolent sexism, and attitudes toward gay men and lesbians. First, the findings demonstrated that boys scored significantly higher on all the variables assessed except on benevolent sexism. Two similar models were obtained for both sexes. Benevolent sexism and, in boys, more positive attitudes toward gay men predicted more negative attitudes toward bullying when mediated by more expressive gender traits. An inverse pattern was also observed: Hostile sexism predicted more favorable attitudes toward bullying when mediated by instrumental gender traits. Attitudes toward bullying were highly correlated with bullying behavior. The five-predictor variables (including attitudes toward bullying) explained 58% of the variance of bullying behavior in girls and 37% of such variance in boys.

Genetic control of residual variance of yearling weight in Nellore beef cattle.

PubMed

Iung, L H S; Neves, H H R; Mulder, H A; Carvalheiro, R

2017-04-01

There is evidence for genetic variability in residual variance of livestock traits, which offers the potential for selection for increased uniformity of production. Different statistical approaches have been employed to study this topic; however, little is known about the concordance between them. The aim of our study was to investigate the genetic heterogeneity of residual variance on yearling weight (YW; 291.15 ± 46.67) in a Nellore beef cattle population; to compare the results of the statistical approaches, the two-step approach and the double hierarchical generalized linear model (DHGLM); and to evaluate the effectiveness of power transformation to accommodate scale differences. The comparison was based on genetic parameters, accuracy of EBV for residual variance, and cross-validation to assess predictive performance of both approaches. A total of 194,628 yearling weight records from 625 sires were used in the analysis. The results supported the hypothesis of genetic heterogeneity of residual variance on YW in Nellore beef cattle and the opportunity of selection, measured through the genetic coefficient of variation of residual variance (0.10 to 0.12 for the two-step approach and 0.17 for DHGLM, using an untransformed data set). However, low estimates of genetic variance associated with positive genetic correlations between mean and residual variance (about 0.20 for two-step and 0.76 for DHGLM for an untransformed data set) limit the genetic response to selection for uniformity of production while simultaneously increasing YW itself. Moreover, large sire families are needed to obtain accurate estimates of genetic merit for residual variance, as indicated by the low heritability estimates (<0.007). Box-Cox transformation was able to decrease the dependence of the variance on the mean and decreased the estimates of genetic parameters for residual variance. The transformation reduced but did not eliminate all the genetic heterogeneity of residual variance, highlighting its presence beyond the scale effect. The DHGLM showed higher predictive ability of EBV for residual variance and therefore should be preferred over the two-step approach.

Using the Positive and Negative Syndrome Scale (PANSS) to Define Different Domains of Negative Symptoms: Prediction of Everyday Functioning by Impairments in Emotional Expression and Emotional Experience.

PubMed

Harvey, Philip D; Khan, Anzalee; Keefe, Richard S E

2017-12-01

Background: Reduced emotional experience and expression are two domains of negative symptoms. The authors assessed these two domains of negative symptoms using previously developed Positive and Negative Syndrome Scale (PANSS) factors. Using an existing dataset, the authors predicted three different elements of everyday functioning (social, vocational, and everyday activities) with these two factors, as well as with performance on measures of functional capacity. Methods: A large (n=630) sample of people with schizophrenia was used as the data source of this study. Using regression analyses, the authors predicted the three different aspects of everyday functioning, first with just the two Positive and Negative Syndrome Scale factors and then with a global negative symptom factor. Finally, we added neurocognitive performance and functional capacity as predictors. Results: The Positive and Negative Syndrome Scale reduced emotional experience factor accounted for 21 percent of the variance in everyday social functioning, while reduced emotional expression accounted for no variance. The total Positive and Negative Syndrome Scale negative symptom factor accounted for less variance (19%) than the reduced experience factor alone. The Positive and Negative Syndrome Scale expression factor accounted for, at most, one percent of the variance in any of the functional outcomes, with or without the addition of other predictors. Implications: Reduced emotional experience measured with the Positive and Negative Syndrome Scale, often referred to as "avolition and anhedonia," specifically predicted impairments in social outcomes. Further, reduced experience predicted social impairments better than emotional expression or the total Positive and Negative Syndrome Scale negative symptom factor. In this cross-sectional study, reduced emotional experience was specifically related with social outcomes, accounting for essentially no variance in work or everyday activities, and being the sole meaningful predictor of impairment in social outcomes.

Decadal climate prediction in the large ensemble limit

NASA Astrophysics Data System (ADS)

Yeager, S. G.; Rosenbloom, N. A.; Strand, G.; Lindsay, K. T.; Danabasoglu, G.; Karspeck, A. R.; Bates, S. C.; Meehl, G. A.

2017-12-01

In order to quantify the benefits of initialization for climate prediction on decadal timescales, two parallel sets of historical simulations are required: one "initialized" ensemble that incorporates observations of past climate states and one "uninitialized" ensemble whose internal climate variations evolve freely and without synchronicity. In the large ensemble limit, ensemble averaging isolates potentially predictable forced and internal variance components in the "initialized" set, but only the forced variance remains after averaging the "uninitialized" set. The ensemble size needed to achieve this variance decomposition, and to robustly distinguish initialized from uninitialized decadal predictions, remains poorly constrained. We examine a large ensemble (LE) of initialized decadal prediction (DP) experiments carried out using the Community Earth System Model (CESM). This 40-member CESM-DP-LE set of experiments represents the "initialized" complement to the CESM large ensemble of 20th century runs (CESM-LE) documented in Kay et al. (2015). Both simulation sets share the same model configuration, historical radiative forcings, and large ensemble sizes. The twin experiments afford an unprecedented opportunity to explore the sensitivity of DP skill assessment, and in particular the skill enhancement associated with initialization, to ensemble size. This talk will highlight the benefits of a large ensemble size for initialized predictions of seasonal climate over land in the Atlantic sector as well as predictions of shifts in the likelihood of climate extremes that have large societal impact.

Examining the Causal Role of Leptin in Alzheimer Disease: A Mendelian Randomization Study.

PubMed

Romo, Matthew L; Schooling, C Mary

2017-01-01

Observational evidence regarding the role of leptin in Alzheimer disease (AD) is conflicting. We sought to determine the causal role of circulating leptin and soluble plasma leptin receptor (sOB-R) levels in AD using a separate-sample Mendelian randomization study. Single nucleotide polymorphisms (SNPs) independently and solely predictive of log-transformed leptin (rs10487505 [LEP], rs780093 [GCKR], rs900400 [CCNL1], rs6071166 [SLC32A1], and rs6738627 [COBLL1]) and of sOB-R (rs1137101 [LEPR], rs2767485 [LEPR], and rs1751492 [LEPR]) levels (ng/mL) were obtained from 2 previously reported genome-wide association studies. We obtained associations of leptin and sOB-R levels with AD using inverse variance weighting with fixed effects by combining Wald estimates for each SNP. Sensitivity analyses included using weighted median and MR-Egger methods and repeating the analyses using only SNPs of genome-wide significance. Using inverse variance weighting, genetically predicted circulating leptin levels were not associated with AD, albeit with wide confidence intervals (CIs): odds ratio (OR) 0.99 per log-transformed ng/mL; 95% CI 0.55-1.78. Similarly, the association of sOB-R with AD was null using inverse variance weighting (OR 1.08 per log-transformed ng/mL; 95% CI 0.83-1.41). Results from our sensitivity analyses confirmed our findings. In this first Mendelian randomization study estimating the causal effect of leptin on AD, we did not find an effect of genetically predicted circulating leptin and sOB-R levels on AD. As such, this study suggests that leptin is unlikely to be a major contributor to AD, although the wide CIs preclude a definitive assessment. © 2017 S. Karger AG, Basel.

Cross-cultural differences on Gunas and other well-being dimensions.

PubMed

Singh, Kamlesh; Jain, Anjali; Kaur, Jasleen; Junnarkar, Mohita; Slezackova, Alena

2016-12-01

Indian perspective of human nature and personality are often viewed through a trigunas perspective-Sattva, Rajas and Tamas. The current study investigated the triadic gunas and well-being dimensions across 3 nations India (n=493; 194 males and 299 females; mean age=21.73 years, SD=3.23), USA (n=302; 80 males and 222 females; mean age=22.90years, SD=2.78) and Czech Republic (n=353; 67 males and 286 females; mean age=22.29years, SD=2.29) with a total of 1148 participants. Triguna Personality (Vedic Personality inventory) and well- being dimensions measured by Mental Health Continuum- Short Form, Flourishing scale and the Scale of Positive and Negative Experiences (MHC-SF, FS and SPANE) differed across countries. Triguna were correlated with MHC-SF and its clusters, FS and SPANE. Regression analysis revealed that Trigunas accounted significantly for well-being dimensions, for instance, Sattva accounted for 48% variance in Czechs, 56% in Indians and 55% in Americans, Rajas accounted for 21% variance in Czechs, 08% in Indians and 54% in Americans and Tamas accounted for 50% variance in Czechs, 20% in Indians and 64% in Americans. The results reinforce that trigunas personality significantly predict well-being dimensions. Copyright © 2016 Elsevier B.V. All rights reserved.

Do different types of school mathematics development depend on different constellations of numerical versus general cognitive abilities?

PubMed

Fuchs, Lynn S; Geary, David C; Compton, Donald L; Fuchs, Douglas; Hamlett, Carol L; Seethaler, Pamela M; Bryant, Joan D; Schatschneider, Christopher

2010-11-01

The purpose of this study was to examine the interplay between basic numerical cognition and domain-general abilities (such as working memory) in explaining school mathematics learning. First graders (N = 280; mean age = 5.77 years) were assessed on 2 types of basic numerical cognition, 8 domain-general abilities, procedural calculations, and word problems in fall and then reassessed on procedural calculations and word problems in spring. Development was indexed by latent change scores, and the interplay between numerical and domain-general abilities was analyzed by multiple regression. Results suggest that the development of different types of formal school mathematics depends on different constellations of numerical versus general cognitive abilities. When controlling for 8 domain-general abilities, both aspects of basic numerical cognition were uniquely predictive of procedural calculations and word problems development. Yet, for procedural calculations development, the additional amount of variance explained by the set of domain-general abilities was not significant, and only counting span was uniquely predictive. By contrast, for word problems development, the set of domain-general abilities did provide additional explanatory value, accounting for about the same amount of variance as the basic numerical cognition variables. Language, attentive behavior, nonverbal problem solving, and listening span were uniquely predictive.

Modeling the relationship between rapid automatized naming and literacy skills across languages varying in orthographic consistency.

PubMed

Georgiou, George K; Aro, Mikko; Liao, Chen-Huei; Parrila, Rauno

2016-03-01

The purpose of this study was twofold: (a) to contrast the prominent theoretical explanations of the rapid automatized naming (RAN)-reading relationship across languages varying in orthographic consistency (Chinese, English, and Finnish) and (b) to examine whether the same accounts can explain the RAN-spelling relationship. In total, 304 Grade 4 children (102 Chinese-speaking Taiwanese children, 117 English-speaking Canadian children, and 85 Finnish-speaking children) were assessed on measures of RAN, speed of processing, phonological processing, orthographic processing, reading fluency, and spelling. The results of path analysis indicated that RAN had a strong direct effect on reading fluency that was of the same size across languages and that only in English was a small proportion of its predictive variance mediated by orthographic processing. In contrast, RAN did not exert a significant direct effect on spelling, and a substantial proportion of its predictive variance was mediated by phonological processing (in Chinese and Finnish) and orthographic processing (in English). Given that RAN predicted reading fluency equally well across languages and that phonological/orthographic processing had very little to do with this relationship, we argue that the reason why RAN is related to reading fluency should be sought in domain-general factors such as serial processing and articulation. Copyright © 2015 Elsevier Inc. All rights reserved.

Do Different Types of School Mathematics Development Depend on Different Constellations of Numerical versus General Cognitive Abilities?

PubMed Central

Fuchs, Lynn S.; Geary, David C.; Compton, Donald L.; Fuchs, Douglas; Hamlett, Carol L.; Seethaler, Pamela M.; Bryant, Joan D.; Schatschneider, Christopher

2010-01-01

The purpose of this study was to examine the interplay between basic numerical cognition and domain-general abilities (such as working memory) in explaining school mathematics learning. First graders (n=280; 5.77 years) were assessed on 2 types of basic numerical cognition, 8 domain-general abilities, procedural calculations (PCs), and word problems (WPs) in fall and then reassessed on PCs and WPs in spring. Development was indexed via latent change scores, and the interplay between numerical and domain-general abilities was analyzed via multiple regression. Results suggest that the development of different types of formal school mathematics depends on different constellations of numerical versus general cognitive abilities. When controlling for 8 domain-general abilities, both aspects of basic numerical cognition were uniquely predictive of PC and WP development. Yet, for PC development, the additional amount of variance explained by the set of domain-general abilities was not significant, and only counting span was uniquely predictive. By contrast, for WP development, the set of domain- general abilities did provide additional explanatory value, accounting for about the same amount of variance as the basic numerical cognition variables. Language, attentive behavior, nonverbal problem solving, and listening span were uniquely predictive. PMID:20822213

Neuroticism (not depressive symptoms) predicts memory complaints in some community-dwelling older adults.

PubMed

Merema, Matt R; Speelman, Craig P; Foster, Jonathan K; Kaczmarek, Elizabeth A

2013-08-01

To examine whether depressive symptoms are useful predictors of subjective memory complaints in community-dwelling older adults, beyond the predictive utility already provided by memory performance and characteristics of personality. Using hierarchical regression, we examined the relationship between depressive symptoms and subjective memory complaints, controlling for age, gender, education, memory performance, conscientiousness, and neuroticism. Community-dwelling older adults aged 66 to 90 years (N = 177) who responded to a newspaper advertisement for a memory study in Perth, Western Australia. The General Frequency of Forgetting scale (for memory complaints), Depression Anxiety Stress Scales (for depressive symptoms), NEO-Five Factor Inventory (for conscientiousness and neuroticism), and the Visual Reproduction and Logical Memory subtests from the Wechsler Memory Scale-4th Edition (for visual and verbal memory). The hierarchical regression analysis indicated that while depressive symptoms significantly predicted memory complaints after variance associated with age, gender, education, memory performance, and conscientiousness was partialled out, they accounted for almost none of the variance in complaints when neuroticism was partialled out. The well-established relationship between depression and memory complaints may exist in some community-dwelling older adult populations only on account of the manner in which both are associated with neuroticism. Copyright © 2013 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

Preschoolers’ Delay of Gratification Predicts Their Body Mass 30 Years Later

PubMed Central

Schlam, Tanya R.; Wilson, Nicole L.; Shoda, Yuichi; Mischel, Walter; Ayduk, Ozlem

2012-01-01

Objective To assess whether preschoolers’ performance on a delay of gratification task would predict their body mass index (BMI) 30 years later. Study design In the late 1960s/early 1970s, 4-year-olds from a university-affiliated preschool completed the classic delay of gratification task. As part of a longitudinal study, a subset (N = 164, 57% women) completed a follow-up approximately 30 years later and self-reported their height and weight. Data were analyzed using hierarchical regression. Results Performance on the delay of gratification task accounted for a significant portion of variance in BMI (4%, p < .01), over and above the variance accounted for by sex alone (13%). Each additional minute a preschooler delayed gratification predicted a .2 point reduction in BMI in adulthood. Conclusions Delaying gratification longer at 4 years of age was associated with having a lower BMI three decades later. The study is, however, correlational, and it is therefore not possible to make causal inferences regarding the relation between delay duration and BMI. Identifying children with greater difficulty delaying gratification could help detect children at risk of becoming overweight or obese. Interventions that improve self-control in young children have been developed and might reduce children’s risk of becoming overweight while having positive effects on other outcomes important to society. PMID:22906511

Examining the Predictive Validity of a Dynamic Assessment of Decoding to Forecast Response Tier 2 to Intervention

PubMed Central

Cho, Eunsoo; Compton, Donald L.; Fuchs, Doug; Fuchs, Lynn S.; Bouton, Bobette

2013-01-01

The purpose of this study was to examine the role of a dynamic assessment (DA) of decoding in predicting responsiveness to Tier 2 small group tutoring in a response-to-intervention model. First-grade students (n=134) who did not show adequate progress in Tier 1 based on 6 weeks of progress monitoring received Tier 2 small-group tutoring in reading for 14 weeks. Student responsiveness to Tier 2 was assessed weekly with word identification fluency (WIF). A series of conditional individual growth curve analyses were completed that modeled the correlates of WIF growth (final level of performance and growth). Its purpose was to examine the predictive validity of DA in the presence of 3 sets of variables: static decoding measures, Tier 1 responsiveness indicators, and pre-reading variables (phonemic awareness, rapid letter naming, oral vocabulary, and IQ). DA was a significant predictor of final level and growth, uniquely explaining 3% – 13% of the variance in Tier 2 responsiveness depending on the competing predictors in the model and WIF outcome (final level of performance or growth). Although the additional variances explained uniquely by DA were relatively small, results indicate the potential of DA in identifying Tier 2 nonresponders. PMID:23213050

Examining the predictive validity of a dynamic assessment of decoding to forecast response to tier 2 intervention.

PubMed

Cho, Eunsoo; Compton, Donald L; Fuchs, Douglas; Fuchs, Lynn S; Bouton, Bobette

2014-01-01

The purpose of this study was to examine the role of a dynamic assessment (DA) of decoding in predicting responsiveness to Tier 2 small-group tutoring in a response-to-intervention model. First grade students (n = 134) who did not show adequate progress in Tier 1 based on 6 weeks of progress monitoring received Tier 2 small-group tutoring in reading for 14 weeks. Student responsiveness to Tier 2 was assessed weekly with word identification fluency (WIF). A series of conditional individual growth curve analyses were completed that modeled the correlates of WIF growth (final level of performance and growth). Its purpose was to examine the predictive validity of DA in the presence of three sets of variables: static decoding measures, Tier 1 responsiveness indicators, and prereading variables (phonemic awareness, rapid letter naming, oral vocabulary, and IQ). DA was a significant predictor of final level and growth, uniquely explaining 3% to 13% of the variance in Tier 2 responsiveness depending on the competing predictors in the model and WIF outcome (final level of performance or growth). Although the additional variances explained uniquely by DA were relatively small, results indicate the potential of DA in identifying Tier 2 nonresponders. © Hammill Institute on Disabilities 2012.

GPZ: non-stationary sparse Gaussian processes for heteroscedastic uncertainty estimation in photometric redshifts

NASA Astrophysics Data System (ADS)

Almosallam, Ibrahim A.; Jarvis, Matt J.; Roberts, Stephen J.

2016-10-01

The next generation of cosmology experiments will be required to use photometric redshifts rather than spectroscopic redshifts. Obtaining accurate and well-characterized photometric redshift distributions is therefore critical for Euclid, the Large Synoptic Survey Telescope and the Square Kilometre Array. However, determining accurate variance predictions alongside single point estimates is crucial, as they can be used to optimize the sample of galaxies for the specific experiment (e.g. weak lensing, baryon acoustic oscillations, supernovae), trading off between completeness and reliability in the galaxy sample. The various sources of uncertainty in measurements of the photometry and redshifts put a lower bound on the accuracy that any model can hope to achieve. The intrinsic uncertainty associated with estimates is often non-uniform and input-dependent, commonly known in statistics as heteroscedastic noise. However, existing approaches are susceptible to outliers and do not take into account variance induced by non-uniform data density and in most cases require manual tuning of many parameters. In this paper, we present a Bayesian machine learning approach that jointly optimizes the model with respect to both the predictive mean and variance we refer to as Gaussian processes for photometric redshifts (GPZ). The predictive variance of the model takes into account both the variance due to data density and photometric noise. Using the Sloan Digital Sky Survey (SDSS) DR12 data, we show that our approach substantially outperforms other machine learning methods for photo-z estimation and their associated variance, such as TPZ and ANNZ2. We provide a MATLAB and PYTHON implementations that are available to download at https://github.com/OxfordML/GPz.

Constraints on the power spectrum of the primordial density field from large-scale data - Microwave background and predictions of inflation

NASA Technical Reports Server (NTRS)

Kashlinsky, A.

1992-01-01

It is shown here that, by using galaxy catalog correlation data as input, measurements of microwave background radiation (MBR) anisotropies should soon be able to test two of the inflationary scenario's most basic predictions: (1) that the primordial density fluctuations produced were scale-invariant and (2) that the universe is flat. They should also be able to detect anisotropies of large-scale structure formed by gravitational evolution of density fluctuations present at the last scattering epoch. Computations of MBR anisotropies corresponding to the minimum of the large-scale variance of the MBR anisotropy are presented which favor an open universe with P(k) significantly different from the Harrison-Zeldovich spectrum predicted by most inflationary models.

Short-term prediction of rain attenuation level and volatility in Earth-to-Satellite links at EHF band

NASA Astrophysics Data System (ADS)

de Montera, L.; Mallet, C.; Barthès, L.; Golé, P.

2008-08-01

This paper shows how nonlinear models originally developed in the finance field can be used to predict rain attenuation level and volatility in Earth-to-Satellite links operating at the Extremely High Frequencies band (EHF, 20 50 GHz). A common approach to solving this problem is to consider that the prediction error corresponds only to scintillations, whose variance is assumed to be constant. Nevertheless, this assumption does not seem to be realistic because of the heteroscedasticity of error time series: the variance of the prediction error is found to be time-varying and has to be modeled. Since rain attenuation time series behave similarly to certain stocks or foreign exchange rates, a switching ARIMA/GARCH model was implemented. The originality of this model is that not only the attenuation level, but also the error conditional distribution are predicted. It allows an accurate upper-bound of the future attenuation to be estimated in real time that minimizes the cost of Fade Mitigation Techniques (FMT) and therefore enables the communication system to reach a high percentage of availability. The performance of the switching ARIMA/GARCH model was estimated using a measurement database of the Olympus satellite 20/30 GHz beacons and this model is shown to outperform significantly other existing models. The model also includes frequency scaling from the downlink frequency to the uplink frequency. The attenuation effects (gases, clouds and rain) are first separated with a neural network and then scaled using specific scaling factors. As to the resulting uplink prediction error, the error contribution of the frequency scaling step is shown to be larger than that of the downlink prediction, indicating that further study should focus on improving the accuracy of the scaling factor.

Spectrotemporal Modulation Sensitivity as a Predictor of Speech-Reception Performance in Noise With Hearing Aids

PubMed Central

Danielsson, Henrik; Hällgren, Mathias; Stenfelt, Stefan; Rönnberg, Jerker; Lunner, Thomas

2016-01-01

The audiogram predicts <30% of the variance in speech-reception thresholds (SRTs) for hearing-impaired (HI) listeners fitted with individualized frequency-dependent gain. The remaining variance could reflect suprathreshold distortion in the auditory pathways or nonauditory factors such as cognitive processing. The relationship between a measure of suprathreshold auditory function—spectrotemporal modulation (STM) sensitivity—and SRTs in noise was examined for 154 HI listeners fitted with individualized frequency-specific gain. SRTs were measured for 65-dB SPL sentences presented in speech-weighted noise or four-talker babble to an individually programmed master hearing aid, with the output of an ear-simulating coupler played through insert earphones. Modulation-depth detection thresholds were measured over headphones for STM (2cycles/octave density, 4-Hz rate) applied to an 85-dB SPL, 2-kHz lowpass-filtered pink-noise carrier. SRTs were correlated with both the high-frequency (2–6 kHz) pure-tone average (HFA; R2 = .31) and STM sensitivity (R2 = .28). Combined with the HFA, STM sensitivity significantly improved the SRT prediction (ΔR2 = .13; total R2 = .44). The remaining unaccounted variance might be attributable to variability in cognitive function and other dimensions of suprathreshold distortion. STM sensitivity was most critical in predicting SRTs for listeners < 65 years old or with HFA <53 dB HL. Results are discussed in the context of previous work suggesting that STM sensitivity for low rates and low-frequency carriers is impaired by a reduced ability to use temporal fine-structure information to detect dynamic spectra. STM detection is a fast test of suprathreshold auditory function for frequencies <2 kHz that complements the HFA to predict variability in hearing-aid outcomes for speech perception in noise. PMID:27815546

Educational Attainment: A Genome Wide Association Study in 9538 Australians

PubMed Central

Martin, Nicolas W.; Medland, Sarah E.; Verweij, Karin J. H.; Lee, S. Hong; Nyholt, Dale R.; Madden, Pamela A.; Heath, Andrew C.; Montgomery, Grant W.; Wright, Margaret J.; Martin, Nicholas G.

2011-01-01

Background Correlations between Educational Attainment (EA) and measures of cognitive performance are as high as 0.8. This makes EA an attractive alternative phenotype for studies wishing to map genes affecting cognition due to the ease of collecting EA data compared to other cognitive phenotypes such as IQ. Methodology In an Australian family sample of 9538 individuals we performed a genome-wide association scan (GWAS) using the imputed genotypes of ∼2.4 million single nucleotide polymorphisms (SNP) for a 6-point scale measure of EA. Top hits were checked for replication in an independent sample of 968 individuals. A gene-based test of association was then applied to the GWAS results. Additionally we performed prediction analyses using the GWAS results from our discovery sample to assess the percentage of EA and full scale IQ variance explained by the predicted scores. Results The best SNP fell short of having a genome-wide significant p-value (p = 9.77×10−7). In our independent replication sample six SNPs among the top 50 hits pruned for linkage disequilibrium (r2<0.8) had a p-value<0.05 but only one of these SNPs survived correction for multiple testing - rs7106258 (p = 9.7*10−4) located in an intergenic region of chromosome 11q14.1. The gene based test results were non-significant and our prediction analyses show that the predicted scores explained little variance in EA in our replication sample. Conclusion While we have identified a polymorphism chromosome 11q14.1 associated with EA, further replication is warranted. Overall, the absence of genome-wide significant p-values in our large discovery sample confirmed the high polygenic architecture of EA. Only the assembly of large samples or meta-analytic efforts will be able to assess the implication of common DNA polymorphisms in the etiology of EA. PMID:21694764

Utility of the theory of reasoned action and theory of planned behavior for predicting Chinese adolescent smoking.

PubMed

Guo, Qian; Johnson, C Anderson; Unger, Jennifer B; Lee, Liming; Xie, Bin; Chou, Chih-Ping; Palmer, Paula H; Sun, Ping; Gallaher, Peggy; Pentz, MaryAnn

2007-05-01

One third of smokers worldwide live in China. Identifying predictors of smoking is important for prevention program development. This study explored whether the Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB) predict adolescent smoking in China. Data were obtained from 14,434 middle and high school students (48.6% boys, 51.4% girls) in seven geographically varied cities in China. TRA and TPB were tested by multilevel mediation modeling, and compared by multilevel analyses and likelihood ratio tests. Perceived behavioral control was tested as a main effect in TPB and a moderation effect in TRA. The mediation effects of smoking intention were supported in both models (p<0.001). TPB accounted for significantly more variance than TRA (p<0.001). Perceived behavioral control significantly interacted with attitudes and social norms in TRA (p<0.001). Therefore, TRA and TPB are applicable to China to predict adolescent smoking. TPB is superior to TRA for the prediction and TRA can better predict smoking among students with lower than higher perceived behavioral control.

Using social cognitive theory to explain discretionary, "leisure-time" physical exercise among high school students.

PubMed

Winters, Eric R; Petosa, Rick L; Charlton, Thomas E

2003-06-01

To examine whether knowledge of high school students' actions of self-regulation, and perceptions of self-efficacy to overcome exercise barriers, social situation, and outcome expectation will predict non-school related moderate and vigorous physical exercise. High school students enrolled in introductory Physical Education courses completed questionnaires that targeted selected Social Cognitive Theory variables. They also self-reported their typical "leisure-time" exercise participation using a standardized questionnaire. Bivariate correlation statistic and hierarchical regression were conducted on reports of moderate and vigorous exercise frequency. Each predictor variable was significantly associated with measures of moderate and vigorous exercise frequency. All predictor variables were significant in the final regression model used to explain vigorous exercise. After controlling for the effects of gender, the psychosocial variables explained 29% of variance in vigorous exercise frequency. Three of four predictor variables were significant in the final regression equation used to explain moderate exercise. The final regression equation accounted for 11% of variance in moderate exercise frequency. Professionals who attempt to increase the prevalence of physical exercise through educational methods should focus on the psychosocial variables utilized in this study.

THE LONGEST TIMESCALE X-RAY VARIABILITY REVEALS EVIDENCE FOR ACTIVE GALACTIC NUCLEI IN THE HIGH ACCRETION STATE

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

Zhang Youhong, E-mail: youhong.zhang@mail.tsinghua.edu.cn

2011-01-01

The All Sky Monitor (ASM) on board the Rossi X-ray Timing Explorer has continuously monitored a number of active galactic nuclei (AGNs) with similar sampling rates for 14 years, from 1996 January to 2009 December. Utilizing the archival ASM data of 27 AGNs, we calculate the normalized excess variances of the 300-day binned X-ray light curves on the longest timescale (between 300 days and 14 years) explored so far. The observed variance appears to be independent of AGN black-hole mass and bolometric luminosity. According to the scaling relation of black-hole mass (and bolometric luminosity) from galactic black hole X-ray binariesmore » (GBHs) to AGNs, the break timescales that correspond to the break frequencies detected in the power spectral density (PSD) of our AGNs are larger than the binsize (300 days) of the ASM light curves. As a result, the singly broken power-law (soft-state) PSD predicts the variance to be independent of mass and luminosity. Nevertheless, the doubly broken power-law (hard-state) PSD predicts, with the widely accepted ratio of the two break frequencies, that the variance increases with increasing mass and decreases with increasing luminosity. Therefore, the independence of the observed variance on mass and luminosity suggests that AGNs should have soft-state PSDs. Taking into account the scaling of the break timescale with mass and luminosity synchronously, the observed variances are also more consistent with the soft-state than the hard-state PSD predictions. With the averaged variance of AGNs and the soft-state PSD assumption, we obtain a universal PSD amplitude of 0.030 {+-} 0.022. By analogy with the GBH PSDs in the high/soft state, the longest timescale variability supports the standpoint that AGNs are scaled-up GBHs in the high accretion state, as already implied by the direct PSD analysis.« less

Self-regulatory skills usage strengthens the relations of self-efficacy for improved eating, exercise, and weight in the severely obese: toward an explanatory model.

PubMed

Annesi, James J

2011-07-01

Lack of success with behavioral weight-management treatments indicates a need for a better understanding of modifiable psychological correlates. Adults with class 2 and 3 obesity (N = 183; Mean(BMI) = 42.0 kg/m(2)) volunteered for a 26-week nutrition and exercise treatment, based on social cognitive theory, that focused on self-efficacy and self-regulation applied to increasing cardiovascular exercise and fruit and vegetable consumption. Improved self-efficacy for controlled eating significantly predicted increased fruit and vegetable consumption (R(2) = .15). Improved self-efficacy for exercise significantly predicted increased exercise (R(2) = .46). When changes in self-regulatory skill usage were stepped into the 2 previous equations, the variances accounted for significantly increased. Increases in fruit and vegetable consumption and exercise significantly predicted weight loss (R(2) = .38). Findings suggest that behavioral theory should guide research on weight-loss treatment, and a focus on self-efficacy and self-regulatory skills applied to specific nutrition and exercise behaviors is warranted.

Predicting attitudes toward seeking professional psychological help among Alaska Natives.

PubMed

Freitas-Murrell, Brittany; Swift, Joshua K

2015-01-01

This study sought to examine the role of current/previous treatment experience, stigma (social and self), and cultural identification (Caucasian and Alaska Native [AN]) in predicting attitudes toward psychological help seeking for ANs. Results indicated that these variables together explained roughly 56% of variance in attitudes. In particular, while self-stigma and identification with the Caucasian culture predicted a unique amount of variance in help-seeking attitudes, treatment use and identification with AN culture did not. The results of this study indicate that efforts to address the experience of self-stigma may prove most useful to improving help-seeking attitudes in ANs.

Predicting Cost and Schedule Growth for Military and Civil Space Systems

DTIC Science & Technology

2008-03-01

the Shapiro-Wilk Test , and testing the residuals for constant variance using the Breusch - Pagan test . For logistic models, diagnostics include...the Breusch - Pagan Test . With this test , a p-value below 0.05 rejects the null hypothesis that the residuals have constant variance. Thus, similar...to the Shapiro- Wilk Test , because the optimal model will have constant variance of its residuals, this requires Breusch - Pagan p-values over 0.05

Object Perception Impairments Predict Instrumental Activities of Daily Living Dependence in Alzheimer's Disease

PubMed Central

JEFFERSON, ANGELA L.; BARAKAT, LAMIA P.; GIOVANNETTI, TANIA; PAUL, ROBERT H.; GLOSSER, GUILA

2009-01-01

This study examined the contribution of object perception and spatial localization to functional dependence among Alzheimer's disease (AD) patients. Forty patients with probable AD completed measures assessing verbal recognition memory, working memory, object perception, spatial localization, semantic knowledge, and global cognition. Primary caregivers completed a measure of activities of daily living (ADLs) that included instrumental and basic self-care subscales (i.e., IADLs and BADLs, respectively). Stepwise multiple regressions revealed that global cognition accounted for significant portions of variance among the ADL total, IADL, and BADL scores. However, when global cognition was removed from the model, object perception was the only significant cognitive predictor of the ADL total and IADL subscale scores, accounting for 18.5% and 19.3% of the variance, respectively. When considering multiple cognitive components simultaneously, object perception and the integrity of the inferotemporal cortex is important in the completion of functional abilities in general and IADLs in particular among AD patients. PMID:16822730

Factors Affecting Attachment in International Adoptees at 6 Months Post Adoption

PubMed Central

Weiss, Sandra

2011-01-01

This pilot study examined the effect of five child and maternal factors on the attachment security of international adoptees at six months post adoption. Results from the sample of 22 adoptive mother-infant dyads showed that age at adoption, developmental status, length and quality of preadoption care, and maternal attachment representations were not significant predictors of child attachment status. The number of preadoption placements and the child's stress level did significantly predict attachment status, accounting for approximately 40% of the variance in attachment security. Number of preadoption placements uniquely contributed 14% of that variance (p=.007) while stress level uniquely contributed 12% (p=.01). Children who had fewer preadoption placements had higher attachment security; similarly, children who had lower stress levels had higher attachment security. Results suggest that consistency of preadoption care was more important than its length or quality. Further, the relationship between stress level and attachment security raises the possibility that a lower stress level functions as a protective factor for the developing attachment with the adoptive mother. PMID:22267885

Genomic Prediction Accounting for Residual Heteroskedasticity

PubMed Central

Ou, Zhining; Tempelman, Robert J.; Steibel, Juan P.; Ernst, Catherine W.; Bates, Ronald O.; Bello, Nora M.

2015-01-01

Whole-genome prediction (WGP) models that use single-nucleotide polymorphism marker information to predict genetic merit of animals and plants typically assume homogeneous residual variance. However, variability is often heterogeneous across agricultural production systems and may subsequently bias WGP-based inferences. This study extends classical WGP models based on normality, heavy-tailed specifications and variable selection to explicitly account for environmentally-driven residual heteroskedasticity under a hierarchical Bayesian mixed-models framework. WGP models assuming homogeneous or heterogeneous residual variances were fitted to training data generated under simulation scenarios reflecting a gradient of increasing heteroskedasticity. Model fit was based on pseudo-Bayes factors and also on prediction accuracy of genomic breeding values computed on a validation data subset one generation removed from the simulated training dataset. Homogeneous vs. heterogeneous residual variance WGP models were also fitted to two quantitative traits, namely 45-min postmortem carcass temperature and loin muscle pH, recorded in a swine resource population dataset prescreened for high and mild residual heteroskedasticity, respectively. Fit of competing WGP models was compared using pseudo-Bayes factors. Predictive ability, defined as the correlation between predicted and observed phenotypes in validation sets of a five-fold cross-validation was also computed. Heteroskedastic error WGP models showed improved model fit and enhanced prediction accuracy compared to homoskedastic error WGP models although the magnitude of the improvement was small (less than two percentage points net gain in prediction accuracy). Nevertheless, accounting for residual heteroskedasticity did improve accuracy of selection, especially on individuals of extreme genetic merit. PMID:26564950

Probabilistic prediction of barrier-island response to hurricanes

USGS Publications Warehouse

Plant, Nathaniel G.; Stockdon, Hilary F.

2012-01-01

Prediction of barrier-island response to hurricane attack is important for assessing the vulnerability of communities, infrastructure, habitat, and recreational assets to the impacts of storm surge, waves, and erosion. We have demonstrated that a conceptual model intended to make qualitative predictions of the type of beach response to storms (e.g., beach erosion, dune erosion, dune overwash, inundation) can be reformulated in a Bayesian network to make quantitative predictions of the morphologic response. In an application of this approach at Santa Rosa Island, FL, predicted dune-crest elevation changes in response to Hurricane Ivan explained about 20% to 30% of the observed variance. An extended Bayesian network based on the original conceptual model, which included dune elevations, storm surge, and swash, but with the addition of beach and dune widths as input variables, showed improved skill compared to the original model, explaining 70% of dune elevation change variance and about 60% of dune and shoreline position change variance. This probabilistic approach accurately represented prediction uncertainty (measured with the log likelihood ratio), and it outperformed the baseline prediction (i.e., the prior distribution based on the observations). Finally, sensitivity studies demonstrated that degrading the resolution of the Bayesian network or removing data from the calibration process reduced the skill of the predictions by 30% to 40%. The reduction in skill did not change conclusions regarding the relative importance of the input variables, and the extended model's skill always outperformed the original model.

Examining age-related shared variance between face cognition, vision, and self-reported physical health: a test of the common cause hypothesis for social cognition

PubMed Central

Olderbak, Sally; Hildebrandt, Andrea; Wilhelm, Oliver

2015-01-01

The shared decline in cognitive abilities, sensory functions (e.g., vision and hearing), and physical health with increasing age is well documented with some research attributing this shared age-related decline to a single common cause (e.g., aging brain). We evaluate the extent to which the common cause hypothesis predicts associations between vision and physical health with social cognition abilities specifically face perception and face memory. Based on a sample of 443 adults (17–88 years old), we test a series of structural equation models, including Multiple Indicator Multiple Cause (MIMIC) models, and estimate the extent to which vision and self-reported physical health are related to face perception and face memory through a common factor, before and after controlling for their fluid cognitive component and the linear effects of age. Results suggest significant shared variance amongst these constructs, with a common factor explaining some, but not all, of the shared age-related variance. Also, we found that the relations of face perception, but not face memory, with vision and physical health could be completely explained by fluid cognition. Overall, results suggest that a single common cause explains most, but not all age-related shared variance with domain specific aging mechanisms evident. PMID:26321998

On how to avoid input and structural uncertainties corrupt the inference of hydrological parameters using a Bayesian framework

NASA Astrophysics Data System (ADS)

Hernández, Mario R.; Francés, Félix

2015-04-01

One phase of the hydrological models implementation process, significantly contributing to the hydrological predictions uncertainty, is the calibration phase in which values of the unknown model parameters are tuned by optimizing an objective function. An unsuitable error model (e.g. Standard Least Squares or SLS) introduces noise into the estimation of the parameters. The main sources of this noise are the input errors and the hydrological model structural deficiencies. Thus, the biased calibrated parameters cause the divergence model phenomenon, where the errors variance of the (spatially and temporally) forecasted flows far exceeds the errors variance in the fitting period, and provoke the loss of part or all of the physical meaning of the modeled processes. In other words, yielding a calibrated hydrological model which works well, but not for the right reasons. Besides, an unsuitable error model yields a non-reliable predictive uncertainty assessment. Hence, with the aim of prevent all these undesirable effects, this research focuses on the Bayesian joint inference (BJI) of both the hydrological and error model parameters, considering a general additive (GA) error model that allows for correlation, non-stationarity (in variance and bias) and non-normality of model residuals. As hydrological model, it has been used a conceptual distributed model called TETIS, with a particular split structure of the effective model parameters. Bayesian inference has been performed with the aid of a Markov Chain Monte Carlo (MCMC) algorithm called Dream-ZS. MCMC algorithm quantifies the uncertainty of the hydrological and error model parameters by getting the joint posterior probability distribution, conditioned on the observed flows. The BJI methodology is a very powerful and reliable tool, but it must be used correctly this is, if non-stationarity in errors variance and bias is modeled, the Total Laws must be taken into account. The results of this research show that the application of BJI with a GA error model outperforms the hydrological parameters robustness (diminishing the divergence model phenomenon) and improves the reliability of the streamflow predictive distribution, in respect of the results of a bad error model as SLS. Finally, the most likely prediction in a validation period, for both BJI+GA and SLS error models shows a similar performance.

Motion compensation via redundant-wavelet multihypothesis.

PubMed

Fowler, James E; Cui, Suxia; Wang, Yonghui

2006-10-01

Multihypothesis motion compensation has been widely used in video coding with previous attention focused on techniques employing predictions that are diverse spatially or temporally. In this paper, the multihypothesis concept is extended into the transform domain by using a redundant wavelet transform to produce multiple predictions that are diverse in transform phase. The corresponding multiple-phase inverse transform implicitly combines the phase-diverse predictions into a single spatial-domain prediction for motion compensation. The performance advantage of this redundant-wavelet-multihypothesis approach is investigated analytically, invoking the fact that the multiple-phase inverse involves a projection that significantly reduces the power of a dense-motion residual modeled as additive noise. The analysis shows that redundant-wavelet multihypothesis is capable of up to a 7-dB reduction in prediction-residual variance over an equivalent single-phase, single-hypothesis approach. Experimental results substantiate the performance advantage for a block-based implementation.

Noninvasive prediction of shunt operation outcome in idiopathic normal pressure hydrocephalus

PubMed Central

Aoki, Yasunori; Kazui, Hiroaki; Tanaka, Toshihisa; Ishii, Ryouhei; Wada, Tamiki; Ikeda, Shunichiro; Hata, Masahiro; Canuet, Leonides; Katsimichas, Themistoklis; Musha, Toshimitsu; Matsuzaki, Haruyasu; Imajo, Kaoru; Kanemoto, Hideki; Yoshida, Tetsuhiko; Nomura, Keiko; Yoshiyama, Kenji; Iwase, Masao; Takeda, Masatoshi

2015-01-01

Idiopathic normal pressure hydrocephalus (iNPH) is a syndrome characterized by gait disturbance, cognitive deterioration and urinary incontinence in elderly individuals. These symptoms can be improved by shunt operation in some but not all patients. Therefore, discovering predictive factors for the surgical outcome is of great clinical importance. We used normalized power variance (NPV) of electroencephalography (EEG) waves, a sensitive measure of the instability of cortical electrical activity, and found significantly higher NPV in beta frequency band at the right fronto-temporo-occipital electrodes (Fp2, T4 and O2) in shunt responders compared to non-responders. By utilizing these differences, we were able to correctly identify responders and non-responders to shunt operation with a positive predictive value of 80% and a negative predictive value of 88%. Our findings indicate that NPV can be useful in noninvasively predicting the clinical outcome of shunt operation in patients with iNPH. PMID:25585705

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.

Fear of negative appearance evaluation: development and evaluation of a new construct for risk factor work in the field of eating disorders.

PubMed

Lundgren, Jennifer D; Anderson, Drew A; Thompson, Joel Kevin

2004-01-01

The psychometric properties and correlates of a measure designed to assess fear of negative appearance evaluation are presented. In Study 1, 165 college females completed the Fear of Negative Appearance Evaluation Scale [FNAES; Thomas, C.M., Keery, H., Williams, R., & Thompson, J. K. (1998, November). The Fear of Negative Appearance Evaluation Scale: Development and preliminary validation. Paper presented at the annual meeting of the Association for the Advancement of Behavior Therapy, Washington, DC] along with measures of body image, eating disturbance, and depression. Results replicated previous analyses indicating the presence of a single factor, good internal consistency, and significant association with measures of body image and eating disturbance. Additionally, the FNAES accounted for unique variance beyond that explained by general fear of negative evaluation, and other measures of body image and eating disturbance, in the prediction of body shape dysphoria, dietary restraint, and trait anxiety. Study 2 further examined the validity of the FNAES, finding it to correlate significantly with measures of social physique anxiety, body image, eating attitude, and mood. The FNAES did not significantly correlate with body mass index (BMI). Regression analyses found the FNAES to predict levels of body image, eating attitude, and mood beyond variance explained by social physique anxiety. The FNAES appears to measure a conceptually unique aspect of body image that has not been indexed by previous measures and may serve a useful role in risk factor and preventive work.

Neuroticism explains unwanted variance in Implicit Association Tests of personality: possible evidence for an affective valence confound.

PubMed

Fleischhauer, Monika; Enge, Sören; Miller, Robert; Strobel, Alexander; Strobel, Anja

2013-01-01

Meta-analytic data highlight the value of the Implicit Association Test (IAT) as an indirect measure of personality. Based on evidence suggesting that confounding factors such as cognitive abilities contribute to the IAT effect, this study provides a first investigation of whether basic personality traits explain unwanted variance in the IAT. In a gender-balanced sample of 204 volunteers, the Big-Five dimensions were assessed via self-report, peer-report, and IAT. By means of structural equation modeling (SEM), latent Big-Five personality factors (based on self- and peer-report) were estimated and their predictive value for unwanted variance in the IAT was examined. In a first analysis, unwanted variance was defined in the sense of method-specific variance which may result from differences in task demands between the two IAT block conditions and which can be mirrored by the absolute size of the IAT effects. In a second analysis, unwanted variance was examined in a broader sense defined as those systematic variance components in the raw IAT scores that are not explained by the latent implicit personality factors. In contrast to the absolute IAT scores, this also considers biases associated with the direction of IAT effects (i.e., whether they are positive or negative in sign), biases that might result, for example, from the IAT's stimulus or category features. None of the explicit Big-Five factors was predictive for method-specific variance in the IATs (first analysis). However, when considering unwanted variance that goes beyond pure method-specific variance (second analysis), a substantial effect of neuroticism occurred that may have been driven by the affective valence of IAT attribute categories and the facilitated processing of negative stimuli, typically associated with neuroticism. The findings thus point to the necessity of using attribute category labels and stimuli of similar affective valence in personality IATs to avoid confounding due to recoding.

The ties that bind what is known to the recall of what is new.

PubMed

Nelson, D L; Zhang, N

2000-12-01

Cued recall success varies with what people know and with what they do during an episode. This paper focuses on prior knowledge and disentangles the relative effects of 10 features of words and their relationships on cued recall. Results are reported for correlational and multiple regression analyses of data obtained from free association norms and from 29 experiments. The 10 features were only weakly correlated with each other in the norms and, with notable exceptions, in the experiments. The regression analysis indicated that forward cue-to-target strength explained the most variance, followed by backward target-to-cue strength. Target connectivity and set size explained the next most variance, along with mediated cue-to-target strength. Finally, frequency, concreteness, shared associate strength, and cue set size also contributed significantly to recall. Taken together, indices of prior word knowledge explain 49% of the recall variance. Theoretically driven equations that use free association to predict cued recall were also evaluated. Each equation was designed to condense multiple indices of word interconnectivity into a single predictor.

Contributions of Risk and Protective Factors to Prediction of Psychological Symptoms after Traumatic Experiences

PubMed Central

Carlson, Eve B.; Palmieri, Patrick A.; Field, Nigel P.; Dalenberg, Constance J.; Macia, Kathryn S.; Spain, David A.

2016-01-01

Objective Traumatic experiences cause considerable suffering and place a burden on society due to lost productivity, increases in suicidality, violence, criminal behavior, and psychological disorder. The impact of traumatic experiences is complicated because many factors affect individuals’ responses. By employing several methodological improvements, we sought to identify risk factors that would account for a greater proportion of variance in later disorder than prior studies. Method In a sample of 129 traumatically injured hospital patients and family members of injured patients, we studied pre-trauma, time of trauma, and post-trauma psychosocial risk and protective factors hypothesized to influence responses to traumatic experiences and posttraumatic (PT) symptoms (including symptoms of PTSD, depression, negative thinking, and dissociation) two months after trauma. Results The risk factors were all significantly correlated with later PT symptoms, with post-trauma life stress, post-trauma social support, and acute stress symptoms showing the strongest relationships. A hierarchical regression, in which the risk factors were entered in 6 steps based on their occurrence in time, showed the risks accounted for 72% of the variance in later symptoms. Most of the variance in PT symptoms was shared among many risk factors, and pre-trauma and post-trauma risk factors accounted for the most variance. Conclusions Collectively, the risk factors accounted for more variance in later PT symptoms than in previous studies. These risk factors may identify individuals at risk for PT psychological disorders and targets for treatment. PMID:27423351

Anthropometry as a predictor of bench press performance done at different loads.

PubMed

Caruso, John F; Taylor, Skyler T; Lutz, Brant M; Olson, Nathan M; Mason, Melissa L; Borgsmiller, Jake A; Riner, Rebekah D

2012-09-01

The purpose of our study was to examine the ability of anthropometric variables (body mass, total arm length, biacromial width) to predict bench press performance at both maximal and submaximal loads. Our methods required 36 men to visit our laboratory and submit to anthropometric measurements, followed by lifting as much weight as possible in good form one time (1 repetition maximum, 1RM) in the exercise. They made 3 more visits in which they performed 4 sets of bench presses to volitional failure at 1 of 3 (40, 55, or 75% 1RM) submaximal loads. An accelerometer (Myotest Inc., Royal Oak MI) measured peak force, velocity, and power after each submaximal load set. With stepwise multivariate regression, our 3 anthropometric variables attempted to explain significant amounts of variance for 13 bench press performance indices. For criterion measures that reached significance, separate Pearson product moment correlation coefficients further assessed if the strength of association each anthropometric variable had with the criterion was also significant. Our analyses showed that anthropometry explained significant amounts (p < 0.05) of variance for 8 criterion measures. It was concluded that body mass had strong univariate correlations with 1RM and force-related measures, total arm length was moderately associated with 1RM and criterion variables at the lightest load, whereas biacromial width had an inverse relationship with the peak number of repetitions performed per set at the 2 lighter loads. Practical applications suggest results may help coaches and practitioners identify anthropometric features that may best predict various measures of bench press prowess in athletes.

Variance and Predictability of Precipitation at Seasonal-to-Interannual Timescales

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Suarez, Max J.; Heiser, Mark

1999-01-01

A series of atmospheric general circulation model (AGCM) simulations, spanning a total of several thousand years, is used to assess the impact of land-surface and ocean boundary conditions on the seasonal-to-interannual variability and predictability of precipitation in a coupled modeling system. In the first half of the analysis, which focuses on precipitation variance, we show that the contributions of ocean, atmosphere, and land processes to this variance can be characterized, to first order, with a simple linear model. This allows a clean separation of the contributions, from which we find: (1) land and ocean processes have essentially different domains of influence, i.e., the amplification of precipitation variance by land-atmosphere feedback is most important outside of the regions (mainly in the tropics) that are most affected by sea surface temperatures; and (2) the strength of land-atmosphere feedback in a given region is largely controlled by the relative availability of energy and water there. In the second half of the analysis, the potential for seasonal-to-interannual predictability of precipitation is quantified under the assumption that all relevant surface boundary conditions (in the ocean and on land) are known perfectly into the future. We find that the chaotic nature of the atmospheric circulation imposes fundamental limits on predictability in many extratropical regions. Associated with this result is an indication that soil moisture initialization or assimilation in a seasonal-to-interannual forecasting system would be beneficial mainly in transition zones between dry and humid regions.

Evaluation of data transformations used with the square root and schoolfield models for predicting bacterial growth rate.

PubMed Central

Alber, S A; Schaffner, D W

1992-01-01

A comparison was made between mathematical variations of the square root and Schoolfield models for predicting growth rate as a function of temperature. The statistical consequences of square root and natural logarithm transformations of growth rate use in several variations of the Schoolfield and square root models were examined. Growth rate variances of Yersinia enterocolitica in brain heart infusion broth increased as a function of temperature. The ability of the two data transformations to correct for the heterogeneity of variance was evaluated. A natural logarithm transformation of growth rate was more effective than a square root transformation at correcting for the heterogeneity of variance. The square root model was more accurate than the Schoolfield model when both models used natural logarithm transformation. PMID:1444367

The California Verbal Learning Test-Children's Version: relation to factor indices of the Wechsler Intelligence Scale for Children-Third Edition.

PubMed

O'Jile, Judith R; Schrimsher, Gregory W; O'Bryant, Sid E

2005-10-01

The California Verbal Learning Test-Children's Version (CVLT-C) provides clinicians with a method of assessing various aspects of children's verbal memory and has been found to be sensitive to memory deficits resulting from a variety of neurological conditions. Intuitively, the CVLT-C would be expected to be highly related to a child's verbal cognitive abilities; however, with only a few exceptions, the relationship of this test to various domains of cognitive function has not been broadly studied empirically. To examine this issue, we evaluated the amount of unique variance in CVLT-C scores that could be predicted by the Verbal Comprehension, Perceptual Organization, Freedom from Distractibility, and Processing Speed indices of the Wechsler Intelligence Scale for Children, Third Edition (WISC-III) beyond that accounted for by age and gender in a sample of 62 children referred to an outpatient psychiatry clinic for neuropsychological evaluation. While the Processing Speed Index predicted a significant amount of variance for both short and long delay free and cued recall, the Verbal Comprehension Index was a poor predictor of CVLT-C performance on all outcome variables, accounting for only 1.5 to 4.5% additional variance above age and gender. These findings indicate that while the CVLT-C may be relatively independent of influences of verbal intelligence and abstract verbal reasoning, general speed and efficiency of processing play an important role in successful encoding for later retrieval on the CVLT-C.

Traumatic dissociation as a predictor of posttraumatic stress disorder in South African female rape survivors.

PubMed

Nöthling, Jani; Lammers, Kees; Martin, Lindi; Seedat, Soraya

2015-04-01

Women survivors of rape are at an increased risk for posttraumatic stress disorder (PTSD). Traumatic dissociation has been identified as a precursor of PTSD. This study assessed the predictive potential of traumatic dissociation in PTSD and depression development.The study followed a longitudinal, prospective design. Ninety-seven female rape survivors were recruited from 2 clinics in Cape Town, South Africa. Clinical interviews and symptom status assessments of the participants were completed to measure dissociation, childhood traumas, resilience, depression, and PTSD.Traumatic dissociation was a significant predictor of PTSD and depression. The linear combination of prior dissociation, current dissociation, and resilience significantly explained 20.7% of the variance in PTSD. Dissociation mediated the relationship between resilience and PTSD.As traumatic dissociation significantly predicts PTSD, its early identification and management may reduce the risk of developing PTSD. Interventions focused on promoting resilience may also be successful in reducing the risk of dissociation following rape.

Forecasting Total Water Storage Changes in the Amazon basin using Atlantic and Pacific Sea Surface Temperatures

NASA Astrophysics Data System (ADS)

De Linage, C.; Famiglietti, J. S.; Randerson, J. T.

2013-12-01

Floods and droughts frequently affect the Amazon River basin, impacting the transportation, river navigation, agriculture, economy and the carbon balance and biodiversity of several South American countries. The present study aims to find the main variables controlling the natural interannual variability of terrestrial water storage in the Amazon region and to propose a modeling framework for flood and drought forecasting. We propose three simple empirical models using a linear combination of lagged spatial averages of central Pacific (Niño 4 index) and tropical North Atlantic (TNAI index) sea surface temperatures (SST) to predict a decade-long record of 3°, monthly terrestrial water storage anomalies (TWSA) observed by the Gravity Recovery And Climate Experiment (GRACE) mission. In addition to a SST forcing term, the models included a relaxation term to simulate the memory of water storage anomalies in response to external variability in forcing. Model parameters were spatially-variable and individually optimized for each 3° grid cell. We also investigated the evolution of the predictive capability of our models with increasing minimum lead times for TWSA forecasts. TNAI was the primary external forcing for the central and western regions of the southern Amazon (35% of variance explained with a 3-month forecast), whereas Niño 4 was dominant in the northeastern part of the basin (61% of variance explained with a 3-month forecast). Forcing the model with a combination of the two indices improved the fit significantly (p<0.05) for at least 64% of the grid cells, compared to models forced solely with Niño 4 or TNAI. The combined model was able to explain 43% of the variance in the Amazon basin as a whole with a 3-month lead time. While 66% of the observed variance was explained in the northeastern Amazon, only 39% of the variance was captured by the combined model in the central and western regions, suggesting that other, more local, forcing sources were important in these regions. The predictive capability of the combined model was monotonically degraded with increasing lead times. Degradation was smaller in the northeastern Amazon (where 49% of the variance was explained using a 8-month lead time versus 69% for a 1 month lead time) compared to the western and central regions of southern Amazon (where 22% of the variance was explained at 8 months versus 43% at 1 month). Our model may provide early warning information about flooding in the northeastern region of the Amazon basin, where floodplain areas are extensive and the sensitivity of floods to external SST forcing was shown to be high. This work also strengthens our understanding of the mechanisms regulating interannual variability in Amazon fires, as TWSA deficits may subsequently lead to atmospheric water vapor deficits and reduced cloudiness via water-limited evapotranspiration. Finally, this work helps to bridge the gap between the current GRACE mission and the follow-on gravity mission.

Mapping multi-scale vascular plant richness in a forest landscape with integrated LiDAR and hyperspectral remote-sensing.

PubMed

Hakkenberg, C R; Zhu, K; Peet, R K; Song, C

2018-02-01

The central role of floristic diversity in maintaining habitat integrity and ecosystem function has propelled efforts to map and monitor its distribution across forest landscapes. While biodiversity studies have traditionally relied largely on ground-based observations, the immensity of the task of generating accurate, repeatable, and spatially-continuous data on biodiversity patterns at large scales has stimulated the development of remote-sensing methods for scaling up from field plot measurements. One such approach is through integrated LiDAR and hyperspectral remote-sensing. However, despite their efficiencies in cost and effort, LiDAR-hyperspectral sensors are still highly constrained in structurally- and taxonomically-heterogeneous forests - especially when species' cover is smaller than the image resolution, intertwined with neighboring taxa, or otherwise obscured by overlapping canopy strata. In light of these challenges, this study goes beyond the remote characterization of upper canopy diversity to instead model total vascular plant species richness in a continuous-cover North Carolina Piedmont forest landscape. We focus on two related, but parallel, tasks. First, we demonstrate an application of predictive biodiversity mapping, using nonparametric models trained with spatially-nested field plots and aerial LiDAR-hyperspectral data, to predict spatially-explicit landscape patterns in floristic diversity across seven spatial scales between 0.01-900 m 2 . Second, we employ bivariate parametric models to test the significance of individual, remotely-sensed predictors of plant richness to determine how parameter estimates vary with scale. Cross-validated results indicate that predictive models were able to account for 15-70% of variance in plant richness, with LiDAR-derived estimates of topography and forest structural complexity, as well as spectral variance in hyperspectral imagery explaining the largest portion of variance in diversity levels. Importantly, bivariate tests provide evidence of scale-dependence among predictors, such that remotely-sensed variables significantly predict plant richness only at spatial scales that sufficiently subsume geolocational imprecision between remotely-sensed and field data, and best align with stand components including plant size and density, as well as canopy gaps and understory growth patterns. Beyond their insights into the scale-dependent patterns and drivers of plant diversity in Piedmont forests, these results highlight the potential of remotely-sensible essential biodiversity variables for mapping and monitoring landscape floristic diversity from air- and space-borne platforms. © 2017 by the Ecological Society of America.

Prediction of flow duration curves for ungauged basins

NASA Astrophysics Data System (ADS)

Atieh, Maya; Taylor, Graham; M. A. Sattar, Ahmed; Gharabaghi, Bahram

2017-02-01

This study presents novel models for prediction of flow Duration Curves (FDCs) at ungauged basins using artificial neural networks (ANN) and Gene Expression Programming (GEP) trained and tested using historical flow records from 171 unregulated and 89 regulated basins across North America. For the 89 regulated basins, FDCs were generated for both before and after flow regulation. Topographic, climatic, and land use characteristics are used to develop relationships between these basin characteristics and FDC statistical distribution parameters: mean (m) and variance (ν). The two main hypotheses that flow regulation has negligible effect on the mean (m) while it the variance (ν) were confirmed. The novel GEP model that predicts the mean (GEP-m) performed very well with high R2 (0.9) and D (0.95) values and low RAE value of 0.25. The simple regression model that predicts the variance (REG-v) was developed as a function of the mean (m) and a flow regulation index (R). The measured performance and uncertainty analysis indicated that the ANN-m was the best performing model with R2 (0.97), RAE (0.21), D (0.93) and the lowest 95% confidence prediction error interval (+0.22 to +3.49). Both GEP and ANN models were most sensitive to drainage area followed by mean annual precipitation, apportionment entropy disorder index, and shape factor.

On climate prediction: how much can we expect from climate memory?

NASA Astrophysics Data System (ADS)

Yuan, Naiming; Huang, Yan; Duan, Jianping; Zhu, Congwen; Xoplaki, Elena; Luterbacher, Jürg

2018-03-01

Slowing variability in climate system is an important source of climate predictability. However, it is still challenging for current dynamical models to fully capture the variability as well as its impacts on future climate. In this study, instead of simulating the internal multi-scale oscillations in dynamical models, we discussed the effects of internal variability in terms of climate memory. By decomposing climate state x(t) at a certain time point t into memory part M(t) and non-memory part ɛ (t) , climate memory effects from the past 30 years on climate prediction are quantified. For variables with strong climate memory, high variance (over 20% ) in x(t) is explained by the memory part M(t), and the effects of climate memory are non-negligible for most climate variables, but the precipitation. Regarding of multi-steps climate prediction, a power law decay of the explained variance was found, indicating long-lasting climate memory effects. The explained variances by climate memory can remain to be higher than 10% for more than 10 time steps. Accordingly, past climate conditions can affect both short (monthly) and long-term (interannual, decadal, or even multidecadal) climate predictions. With the memory part M(t) precisely calculated from Fractional Integral Statistical Model, one only needs to focus on the non-memory part ɛ (t) , which is an important quantity that determines climate predictive skills.

Bilateral Versus Unilateral Cochlear Implants in Children: A Study of Spoken Language Outcomes

PubMed Central

Harris, David; Bennet, Lisa; Bant, Sharyn

2014-01-01

Objectives: Although it has been established that bilateral cochlear implants (CIs) offer additional speech perception and localization benefits to many children with severe to profound hearing loss, whether these improved perceptual abilities facilitate significantly better language development has not yet been clearly established. The aims of this study were to compare language abilities of children having unilateral and bilateral CIs to quantify the rate of any improvement in language attributable to bilateral CIs and to document other predictors of language development in children with CIs. Design: The receptive vocabulary and language development of 91 children was assessed when they were aged either 5 or 8 years old by using the Peabody Picture Vocabulary Test (fourth edition), and either the Preschool Language Scales (fourth edition) or the Clinical Evaluation of Language Fundamentals (fourth edition), respectively. Cognitive ability, parent involvement in children’s intervention or education programs, and family reading habits were also evaluated. Language outcomes were examined by using linear regression analyses. The influence of elements of parenting style, child characteristics, and family background as predictors of outcomes were examined. Results: Children using bilateral CIs achieved significantly better vocabulary outcomes and significantly higher scores on the Core and Expressive Language subscales of the Clinical Evaluation of Language Fundamentals (fourth edition) than did comparable children with unilateral CIs. Scores on the Preschool Language Scales (fourth edition) did not differ significantly between children with unilateral and bilateral CIs. Bilateral CI use was found to predict significantly faster rates of vocabulary and language development than unilateral CI use; the magnitude of this effect was moderated by child age at activation of the bilateral CI. In terms of parenting style, high levels of parental involvement, low amounts of screen time, and more time spent by adults reading to children facilitated significantly better vocabulary and language outcomes. In terms of child characteristics, higher cognitive ability and female sex were predictive of significantly better language outcomes. When family background factors were examined, having tertiary-educated primary caregivers and a family history of hearing loss were significantly predictive of better outcomes. Birth order was also found to have a significant negative effect on both vocabulary and language outcomes, with each older sibling predicting a 5 to 10% decrease in scores. Conclusions: Children with bilateral CIs achieved significantly better vocabulary outcomes, and 8-year-old children with bilateral CIs had significantly better language outcomes than did children with unilateral CIs. These improvements were moderated by children’s ages at both first and second CIs. The outcomes were also significantly predicted by a number of factors related to parenting, child characteristics, and family background. Fifty-one percent of the variance in vocabulary outcomes and between 59 to 69% of the variance in language outcomes was predicted by the regression models. PMID:24557003

Predictors of health-related quality of life of European food-allergic patients.

PubMed

Saleh-Langenberg, J; Goossens, N J; Flokstra-de Blok, B M J; Kollen, B J; van der Meulen, G N; Le, T M; Knulst, A C; Jedrzejczak-Czechowicz, M; Kowalski, M L; Rokicka, E; Starosta, P; de la Hoz Caballer, B; Vazquez-Cortés, S; Cerecedo, I; Barreales, L; Asero, R; Clausen, M; DunnGalvin, A; Hourihane, J O' B; Purohit, A; Papadopoulos, N G; Fernandéz-Rivas, M; Frewer, L; Burney, P; Duiverman, E J; Dubois, A E J

2015-06-01

Although food allergy has universally been found to impair HRQL, studies have found significant differences in HRQL between countries, even when corrected for differences in perceived disease severity. However, little is known about factors other than disease severity which may contribute to HRQL in food-allergic patients. Therefore, the aim of this study was to identify factors which may predict HRQL of food-allergic patients and also to investigate the specific impact of having experienced anaphylaxis and being prescribed an EAI on HRQL. A total of 648 European food-allergic patients (404 adults, 244 children) completed an age-specific questionnaire package including descriptive questions. Multivariable regression analyses were performed to develop models for predicting HRQL of these patients. For adults, the prediction model accounted for 62% of the variance in HRQL and included perceived disease severity, type of symptoms, having a fish or milk allergy, and gender. For children, the prediction model accounted for 28% of the variance in HRQL and included perceived disease severity, having a peanut or soy allergy, and country of origin. For both adults and children, neither experiencing anaphylaxis nor being prescribed an epinephrine auto-injector (EAI) contributed to impairment of HRQL. In this study, food allergy-related HRQL may be predicted to a greater extent in adults than in children. Allergy to certain foods may cause greater HRQL impairment than others. Country of origin may affect HRQL, at least in children. Experiencing anaphylaxis or being prescribed an EAI has no impact on HRQL in either adults or children. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Predicting well-being longitudinally for mothers rearing offspring with intellectual and developmental disabilities.

PubMed

Grein, K A; Glidden, L M

2015-07-01

Well-being outcomes for parents of children with intellectual and developmental disabilities (IDD) may vary from positive to negative at different times and for different measures of well-being. Predicting and explaining this variability has been a major focus of family research for reasons that have both theoretical and applied implications. The current study used data from a 23-year longitudinal investigation of adoptive and birth parents of children with IDD to determine which early child, mother and family characteristics would predict the variance in maternal outcomes 20 years after their original measurement. Using hierarchical regression analyses, we tested the predictive power of variables measured when children were 7 years old on outcomes of maternal well-being when children were 26 years old. Outcome variables included maternal self-report measures of depression and well-being. Final models of well-being accounted for 20% to 34% of variance. For most outcomes, Family Accord and/or the personality variable of Neuroticism (emotional stability/instability) were significant predictors, but some variables demonstrated a different pattern. These findings confirm that (1) characteristics of the child, mother and family during childhood can predict outcomes of maternal well-being 20 years later; and (2) different predictor-outcome relationships can vary substantially, highlighting the importance of using multiple measures to gain a more comprehensive understanding of maternal well-being. These results have implications for refining prognoses for parents and for tailoring service delivery to individual child, parent and family characteristics. © 2014 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Biases in attention, interpretation, memory, and associations in children with varying levels of spider fear: Inter-relations and prediction of behavior.

PubMed

Klein, Anke M; van Niekerk, Rianne; Ten Brink, Giovanni; Rapee, Ronald M; Hudson, Jennifer L; Bögels, Susan M; Becker, Eni S; Rinck, Mike

2017-03-01

Cognitive theories suggest that cognitive biases may be related and together influence the anxiety response. However, little is known about the interrelations of cognitive bias tasks and whether they allow for an improved prediction of fear-related behavior in addition to self-reports. This study simultaneously addressed several types of cognitive biases in children, to investigate attention bias, interpretation bias, memory bias and fear-related associations, their interrelations and the prediction of behavior. Eighty-one children varying in their levels of spider fear completed the Spider Anxiety and Disgust Screening for Children and performed two Emotional Stroop tasks, a Free Recall task, an interpretation task including size and distance indication, an Affective Priming Task, and a Behavioral Assessment Test. We found an attention bias, interpretation bias, and fear-related associations, but no evidence for a memory bias. The biases showed little overlap. Attention bias, interpretation bias, and fear-related associations predicted unique variance in avoidance of spiders. Interpretation bias and fear-related associations remained significant predictors, even when self-reported fear was included as a predictor. Children were not seeking help for their spider fear and were not tested on clinical levels of spider phobia. This is the first study to find evidence that different cognitive biases each predict unique variance in avoidance behavior. Furthermore, it is also the first study in which we found evidence for a relation between fear of spiders and size and distance indication. We showed that this bias is distinct from other cognitive biases. Copyright © 2016 Elsevier Ltd. All rights reserved.

Elimination of trait blocks from multiple trait mixed model equations with singular (Co)variance parameter matrices

USDA-ARS?s Scientific Manuscript database

Transformations to multiple trait mixed model equations (MME) which are intended to improve computational efficiency in best linear unbiased prediction (BLUP) and restricted maximum likelihood (REML) are described. It is shown that traits that are expected or estimated to have zero residual variance...

20180312 - Reproducibility and variance of liver effects in subchronic and chronic repeat dose toxicity studies (SOT)

EPA Science Inventory

In vivo studies provide reference data to evaluate alternative methods for predicting toxicity. However, the reproducibility and variance of effects observed across multiple in vivo studies is not well understood. The US EPA’s Toxicity Reference Database (ToxRefDB) stores d...

Cross-Disorder Genome-Wide Analyses Suggest a Complex Genetic Relationship Between Tourette Syndrome and Obsessive-Compulsive Disorder

PubMed Central

Yu, Dongmei; Mathews, Carol A.; Scharf, Jeremiah M.; Neale, Benjamin M.; Davis, Lea K.; Gamazon, Eric R.; Derks, Eske M.; Evans, Patrick; Edlund, Christopher K.; Crane, Jacquelyn; Fagerness, Jesen A.; Osiecki, Lisa; Gallagher, Patience; Gerber, Gloria; Haddad, Stephen; Illmann, Cornelia; McGrath, Lauren M.; Mayerfeld, Catherine; Arepalli, Sampath; Barlassina, Cristina; Barr, Cathy L.; Bellodi, Laura; Benarroch, Fortu; Berrió, Gabriel Bedoya; Bienvenu, O. Joseph; Black, Donald; Bloch, Michael H.; Brentani, Helena; Bruun, Ruth D.; Budman, Cathy L.; Camarena, Beatriz; Campbell, Desmond D.; Cappi, Carolina; Cardona Silgado, Julio C.; Cavallini, Maria C.; Chavira, Denise A.; Chouinard, Sylvain; Cook, Edwin H.; Cookson, M. R.; Coric, Vladimir; Cullen, Bernadette; Cusi, Daniele; Delorme, Richard; Denys, Damiaan; Dion, Yves; Eapen, Valsama; Egberts, Karin; Falkai, Peter; Fernandez, Thomas; Fournier, Eduardo; Garrido, Helena; Geller, Daniel; Gilbert, Donald; Girard, Simon L.; Grabe, Hans J.; Grados, Marco A.; Greenberg, Benjamin D.; Gross-Tsur, Varda; Grünblatt, Edna; Hardy, John; Heiman, Gary A.; Hemmings, Sian M.J.; Herrera, Luis D.; Hezel, Dianne M.; Hoekstra, Pieter J.; Jankovic, Joseph; Kennedy, James L.; King, Robert A.; Konkashbaev, Anuar I.; Kremeyer, Barbara; Kurlan, Roger; Lanzagorta, Nuria; Leboyer, Marion; Leckman, James F.; Lennertz, Leonhard; Liu, Chunyu; Lochner, Christine; Lowe, Thomas L.; Lupoli, Sara; Macciardi, Fabio; Maier, Wolfgang; Manunta, Paolo; Marconi, Maurizio; McCracken, James T.; Mesa Restrepo, Sandra C.; Moessner, Rainald; Moorjani, Priya; Morgan, Jubel; Muller, Heike; Murphy, Dennis L.; Naarden, Allan L.; Ochoa, William Cornejo; Ophoff, Roel A.; Pakstis, Andrew J.; Pato, Michele T.; Pato, Carlos N.; Piacentini, John; Pittenger, Christopher; Pollak, Yehuda; Rauch, Scott L.; Renner, Tobias; Reus, Victor I.; Richter, Margaret A.; Riddle, Mark A.; Robertson, Mary M.; Romero, Roxana; Rosário, Maria C.; Rosenberg, David; Ruhrmann, Stephan; Sabatti, Chiara; Salvi, Erika; Sampaio, Aline S.; Samuels, Jack; Sandor, Paul; Service, Susan K.; Sheppard, Brooke; Singer, Harvey S.; Smit, Jan H.; Stein, Dan J.; Strengman, Eric; Tischfield, Jay A.; Turiel, Maurizio; Valencia Duarte, Ana V.; Vallada, Homero; Veenstra-VanderWeele, Jeremy; Walitza, Susanne; Walkup, John; Wang, Ying; Weale, Mike; Weiss, Robert; Wendland, Jens R.; Westenberg, Herman G.M.; Yao, Yin; Hounie, Ana G.; Miguel, Euripedes C.; Nicolini, Humberto; Wagner, Michael; Ruiz-Linares, Andres; Cath, Danielle C.; McMahon, William; Posthuma, Danielle; Oostra, Ben A.; Nestadt, Gerald; Rouleau, Guy A.; Purcell, Shaun; Jenike, Michael A.; Heutink, Peter; Hanna, Gregory L.; Conti, David V.; Arnold, Paul D.; Freimer, Nelson; Stewart, S. Evelyn; Knowles, James A.; Cox, Nancy J.; Pauls, David L.

2014-01-01

Obsessive-compulsive disorder (OCD) and Tourette Syndrome (TS) are highly heritable neurodevelopmental disorders that are thought to share genetic risk factors. However, the identification of definitive susceptibility genes for these etiologically complex disorders remains elusive. Here, we report a combined genome-wide association study (GWAS) of TS and OCD in 2723 cases (1310 with OCD, 834 with TS, 579 with OCD plus TS/chronic tics (CT)), 5667 ancestry-matched controls, and 290 OCD parent-child trios. Although no individual single nucleotide polymorphisms (SNPs) achieved genome-wide significance, the GWAS signals were enriched for SNPs strongly associated with variations in brain gene expression levels, i.e. expression quantitative loci (eQTLs), suggesting the presence of true functional variants that contribute to risk of these disorders. Polygenic score analyses identified a significant polygenic component for OCD (p=2×10−4), predicting 3.2% of the phenotypic variance in an independent data set. In contrast, TS had a smaller, non-significant polygenic component, predicting only 0.6% of the phenotypic variance (p=0.06). No significant polygenic signal was detected across the two disorders, although the sample is likely underpowered to detect a modest shared signal. Furthermore, the OCD polygenic signal was significantly attenuated when cases with both OCD and TS/CT were included in the analysis (p=0.01). Previous work has shown that TS and OCD have some degree of shared genetic variation. However, the data from this study suggest that there are also distinct components to the genetic architectures of TS and OCD. Furthermore, OCD with co-occurring TS/CT may have different underlying genetic susceptibility compared to OCD alone. PMID:25158072

Re-analysis of the association of temperature or sunshine with hyperthymic temperament using lithium levels of drinking water.

PubMed

Matsuzaki, Hideki; Terao, Takeshi; Inoue, Takeshi; Takaesu, Yoshikazu; Ishii, Nobuyoshi; Kohno, Kentaro; Takeshima, Minoru; Baba, Hajime; Honma, Hiroshi

2017-12-01

The Japanese archipelago stretches over 4000km from north to south and has four large islands: Hokkaido, Honshu, Shikoku, and Kyushu. Previously, using the Temperament Evaluation of Memphis, Pisa, Paris and San Diego-auto questionnaire version (TEMPS-A), we compared the hyperthymic scores of residents in Sapporo, Obihiro, Takaoka, Koshigaya, and Oita cities (which are located at latitudes of 43°N, 42°N, 36°N, 36°N and 33°N with various combinations of ambient temperament and sunshine in Japan, respectively). We found that latitude predicted significant variance in hyperthymic temperament, and that ambient temperature, but not sunshine, significantly affected hyperthymic temperament scores. However, the analysis failed to consider the effects of naturally occurring low-dose lithium on temperament. In addition to the TEMPS-A data previously collected, we measured lithium levels of the five cities. The effect of temperature, sunshine, and lithium levels on hyperthymic temperament was analyzed for the five cities. A stepwise multiple regression analysis revealed that lithium levels as well as latitude, but not temperature or sunshine, predicted significant variance in hyperthymic temperament scores. Hyperthymic temperament scores were significantly and positively associated with lithium levels whereas they were significantly and negatively associated with latitude. The light, temperature, lithium exposure that residents actually received was not measured. The number of regions studied was limited. The findings might not be generalized to residents across Japan or other countries. The present findings suggest that lithium in drinking water may positively maintain hyperthymic temperament, and that latitude may negatively maintain it. Copyright © 2017 Elsevier B.V. All rights reserved.

Examining Suicide Protective Factors Among Black College Students

PubMed Central

Wang, Mei-Chuan; Lightsey, Owen Richard; Tran, Kimberly K.; Bonaparte, Taria S.

2012-01-01

The purpose of this study was to contribute to the nascent literature on resilience and suicidality among Black Americans by examining factors that may predict less suicidal behavior among this population. We hypothesized that reasons for living, life satisfaction, and religious awareness would account for unique variance in suicidal thoughts and behavior among Black Americans, above the variance accounted for by depressive symptoms. We also hypothesized that reasons for living and religious awareness would be stronger inverse predictors among Black women than Black men. Results indicated that both depression and life satisfaction were stronger predictors of suicidal behavior among Black men. Among women, only reasons for living was a significant inverse predictor of suicidal thoughts and behavior. More frequent reasons for living moderated the relationship between depression and suicidal thoughts and behavior among Black women. PMID:24524434

Predicting general practice attendance for follow-up cancer care.

PubMed

Ngune, Irene; Jiwa, Moyez; McManus, Alexandra; Parsons, Richard; Hodder, Rupert

2015-03-01

To examine the role of the theory of planned behavior (TPB) in influencing patients' intention to attend follow-up visits with a general practitioner (GP). A questionnaire based on the TPB was used to assess colorectal cancer (CRC) patients' intention to attend follow-up visits with a GP. TPB factors accounted for 43.3% of the variance of intention for follow-up visits. Attitude alone explained 23.3% of the variance. Attitude and presence of other comorbidities significantly affected intention to visit a GP (attitude: R(2)=0.23, F [1, 65]=4.35, p < .01; comorbidity: R(2)=0.13, F [1, 65]=3.02, p < .05). Patients who believe their GP has the skills and knowledge to detect a recurrence and patients with other comorbidities have greater intention to visit their GP following treatment.

Prediction of Chinese Drivers' Intentions to Park Illegally in Emergency Lanes: An Application of the Theory of Planned Behavior.

PubMed

Zheng, Yubing; Ma, Yang; Guo, Lixin; Cheng, Jianchuan; Zhang, Yunlong

2018-06-21

Illegal parking in emergency lanes (paved highway shoulders) is becoming a serious road safety issue in China. The aim of this study was: 1) to examine the utility of the theory of planned behavior (TPB) extended with descriptive norm, past behavior, facilitating and deterring circumstances, sensation seeking and invulnerability in predicting Chinese drivers' intentions in illegal emergency lane parking; 2) to investigate whether respondents' demographic characteristics would impact their views towards the behavior and predictive patterns of intentions; 3) to identify significant predictors of intentions. In this cross-sectional study, eligible respondents were all qualified Chinese drivers. A self-administered questionnaire was employed to collect data including demographic information, descriptive norm, past behavior, facilitating and deterring circumstances, sensation seeking and scenario-based invulnerability combined with TPB constructs. Descriptive statistics, MANOVAs and a series of hierarchical multiple linear regression analyses were conducted in SPSS. A total of 435 qualified drivers (234 males and 201 females) with a mean age of 35.2 years (S.D.=10.3) were included in analysis. The descriptive analysis showed that most participants reported weak intentions (M = 2.35) to park illegally in emergency lanes with negative attitude (M = 3.19), low perceived support (M = 2.91) and high control (M = 5.08) over the behavior. The model succeeded in explaining 64% of the variance in intentions for the whole sample, and principal TPB components accounted for 21% of variance in intentions after demographic variables were controlled. MANOVAs revealed that significant differences of respondents' opinions towards illegal emergency lane parking were only found between better-educated drivers (with college education background) and less-educated ones. Separate regression analyses revealed that predictive pattern of better-educated participants also differed significantly from that of less-educated ones. The study revealed that perceived behavioral control, past behavior, facilitating circumstance and invulnerability emerged as consistently significant predictors of Chinese drivers' intentions to park illegally in emergency lanes. Findings of this study may have some practical implications in developing multi-faced interventions or education process for illegal emergency lane parking in China.

Adjusting for Health Status in Non-Linear Models of Health Care Disparities

PubMed Central

Cook, Benjamin L.; McGuire, Thomas G.; Meara, Ellen; Zaslavsky, Alan M.

2009-01-01

This article compared conceptual and empirical strengths of alternative methods for estimating racial disparities using non-linear models of health care access. Three methods were presented (propensity score, rank and replace, and a combined method) that adjust for health status while allowing SES variables to mediate the relationship between race and access to care. Applying these methods to a nationally representative sample of blacks and non-Hispanic whites surveyed in the 2003 and 2004 Medical Expenditure Panel Surveys (MEPS), we assessed the concordance of each of these methods with the Institute of Medicine (IOM) definition of racial disparities, and empirically compared the methods' predicted disparity estimates, the variance of the estimates, and the sensitivity of the estimates to limitations of available data. The rank and replace and combined methods (but not the propensity score method) are concordant with the IOM definition of racial disparities in that each creates a comparison group with the appropriate marginal distributions of health status and SES variables. Predicted disparities and prediction variances were similar for the rank and replace and combined methods, but the rank and replace method was sensitive to limitations on SES information. For all methods, limiting health status information significantly reduced estimates of disparities compared to a more comprehensive dataset. We conclude that the two IOM-concordant methods were similar enough that either could be considered in disparity predictions. In datasets with limited SES information, the combined method is the better choice. PMID:20352070

Understanding academic clinicians’ intent to treat pediatric obesity

PubMed Central

Frankfurter, Claudia; Cunningham, Charles; Morrison, Katherine M; Rimas, Heather; Bailey, Karen

2017-01-01

AIM To examine the extent to which the theory of planned behavior (TPB) predicts academic clinicians’ intent to treat pediatric obesity. METHODS A multi-disciplinary panel iteratively devised a Likert scale survey based on the constructs of the TPB applied to a set of pediatric obesity themes. A cross-sectional electronic survey was then administered to academic clinicians at tertiary care centers across Canada from January to April 2012. Descriptive statistics were used to summarize demographic and item agreement data. A hierarchical linear regression analysis controlling for demographic variables was conducted to examine the extent to which the TPB subscales predicted intent to treat pediatric obesity. RESULTS A total of 198 physicians, surgeons, and allied health professionals across Canada (British Columbia, Alberta, Manitoba, Saskatchewan, Nova Scotia, Ontario and Quebec) completed the survey. On step 1, demographic factors accounted for 7.4% of the variance in intent scores. Together in step 2, demographic variables and TPB subscales predicted 56.9% of the variance in a measure of the intent to treat pediatric obesity. Perceived behavioral control, that is, confidence in one’s ability to manage pediatric obesity, and subjective norms, congruent with one’s context of practice, were the most significant predictors of the intent to treat pediatric obesity. Attitudes and barriers did not predict the intent to treat pediatric obesity in this context. CONCLUSION Enhancing self-confidence in the ability to treat pediatric obesity and the existence of supportive treatment environments are important to increase clinician’s intent to treat pediatric obesity. PMID:28224097

Understanding academic clinicians' intent to treat pediatric obesity.

PubMed

Frankfurter, Claudia; Cunningham, Charles; Morrison, Katherine M; Rimas, Heather; Bailey, Karen

2017-02-08

To examine the extent to which the theory of planned behavior (TPB) predicts academic clinicians' intent to treat pediatric obesity. A multi-disciplinary panel iteratively devised a Likert scale survey based on the constructs of the TPB applied to a set of pediatric obesity themes. A cross-sectional electronic survey was then administered to academic clinicians at tertiary care centers across Canada from January to April 2012. Descriptive statistics were used to summarize demographic and item agreement data. A hierarchical linear regression analysis controlling for demographic variables was conducted to examine the extent to which the TPB subscales predicted intent to treat pediatric obesity. A total of 198 physicians, surgeons, and allied health professionals across Canada (British Columbia, Alberta, Manitoba, Saskatchewan, Nova Scotia, Ontario and Quebec) completed the survey. On step 1, demographic factors accounted for 7.4% of the variance in intent scores. Together in step 2, demographic variables and TPB subscales predicted 56.9% of the variance in a measure of the intent to treat pediatric obesity. Perceived behavioral control, that is, confidence in one's ability to manage pediatric obesity, and subjective norms, congruent with one's context of practice, were the most significant predictors of the intent to treat pediatric obesity. Attitudes and barriers did not predict the intent to treat pediatric obesity in this context. Enhancing self-confidence in the ability to treat pediatric obesity and the existence of supportive treatment environments are important to increase clinician's intent to treat pediatric obesity.

Quantitative parameters of CT texture analysis as potential markersfor early prediction of spontaneous intracranial hemorrhage enlargement.

PubMed

Shen, Qijun; Shan, Yanna; Hu, Zhengyu; Chen, Wenhui; Yang, Bing; Han, Jing; Huang, Yanfang; Xu, Wen; Feng, Zhan

2018-04-30

To objectively quantify intracranial hematoma (ICH) enlargement by analysing the image texture of head CT scans and to provide objective and quantitative imaging parameters for predicting early hematoma enlargement. We retrospectively studied 108 ICH patients with baseline non-contrast computed tomography (NCCT) and 24-h follow-up CT available. Image data were assessed by a chief radiologist and a resident radiologist. Consistency analysis between observers was tested. The patients were divided into training set (75%) and validation set (25%) by stratified sampling. Patients in the training set were dichotomized according to 24-h hematoma expansion ≥ 33%. Using the Laplacian of Gaussian bandpass filter, we chose different anatomical spatial domains ranging from fine texture to coarse texture to obtain a series of derived parameters (mean grayscale intensity, variance, uniformity) in order to quantify and evaluate all data. The parameters were externally validated on validation set. Significant differences were found between the two groups of patients within variance at V 1.0 and in uniformity at U 1.0 , U 1.8 and U 2.5 . The intraclass correlation coefficients for the texture parameters were between 0.67 and 0.99. The area under the ROC curve between the two groups of ICH cases was between 0.77 and 0.92. The accuracy of validation set by CTTA was 0.59-0.85. NCCT texture analysis can objectively quantify the heterogeneity of ICH and independently predict early hematoma enlargement. • Heterogeneity is helpful in predicting ICH enlargement. • CTTA could play an important role in predicting early ICH enlargement. • After filtering, fine texture had the best diagnostic performance. • The histogram-based uniformity parameters can independently predict ICH enlargement. • CTTA is more objective, more comprehensive, more independently operable, than previous methods.

Simultaneous estimation of cross-validation errors in least squares collocation applied for statistical testing and evaluation of the noise variance components

NASA Astrophysics Data System (ADS)

Behnabian, Behzad; Mashhadi Hossainali, Masoud; Malekzadeh, Ahad

2018-02-01

The cross-validation technique is a popular method to assess and improve the quality of prediction by least squares collocation (LSC). We present a formula for direct estimation of the vector of cross-validation errors (CVEs) in LSC which is much faster than element-wise CVE computation. We show that a quadratic form of CVEs follows Chi-squared distribution. Furthermore, a posteriori noise variance factor is derived by the quadratic form of CVEs. In order to detect blunders in the observations, estimated standardized CVE is proposed as the test statistic which can be applied when noise variances are known or unknown. We use LSC together with the methods proposed in this research for interpolation of crustal subsidence in the northern coast of the Gulf of Mexico. The results show that after detection and removing outliers, the root mean square (RMS) of CVEs and estimated noise standard deviation are reduced about 51 and 59%, respectively. In addition, RMS of LSC prediction error at data points and RMS of estimated noise of observations are decreased by 39 and 67%, respectively. However, RMS of LSC prediction error on a regular grid of interpolation points covering the area is only reduced about 4% which is a consequence of sparse distribution of data points for this case study. The influence of gross errors on LSC prediction results is also investigated by lower cutoff CVEs. It is indicated that after elimination of outliers, RMS of this type of errors is also reduced by 19.5% for a 5 km radius of vicinity. We propose a method using standardized CVEs for classification of dataset into three groups with presumed different noise variances. The noise variance components for each of the groups are estimated using restricted maximum-likelihood method via Fisher scoring technique. Finally, LSC assessment measures were computed for the estimated heterogeneous noise variance model and compared with those of the homogeneous model. The advantage of the proposed method is the reduction in estimated noise levels for those groups with the fewer number of noisy data points.

Behavior of sensitivities in the one-dimensional advection-dispersion equation: Implications for parameter estimation and sampling design

USGS Publications Warehouse

Knopman, Debra S.; Voss, Clifford I.

1987-01-01

The spatial and temporal variability of sensitivities has a significant impact on parameter estimation and sampling design for studies of solute transport in porous media. Physical insight into the behavior of sensitivities is offered through an analysis of analytically derived sensitivities for the one-dimensional form of the advection-dispersion equation. When parameters are estimated in regression models of one-dimensional transport, the spatial and temporal variability in sensitivities influences variance and covariance of parameter estimates. Several principles account for the observed influence of sensitivities on parameter uncertainty. (1) Information about a physical parameter may be most accurately gained at points in space and time with a high sensitivity to the parameter. (2) As the distance of observation points from the upstream boundary increases, maximum sensitivity to velocity during passage of the solute front increases and the consequent estimate of velocity tends to have lower variance. (3) The frequency of sampling must be “in phase” with the S shape of the dispersion sensitivity curve to yield the most information on dispersion. (4) The sensitivity to the dispersion coefficient is usually at least an order of magnitude less than the sensitivity to velocity. (5) The assumed probability distribution of random error in observations of solute concentration determines the form of the sensitivities. (6) If variance in random error in observations is large, trends in sensitivities of observation points may be obscured by noise and thus have limited value in predicting variance in parameter estimates among designs. (7) Designs that minimize the variance of one parameter may not necessarily minimize the variance of other parameters. (8) The time and space interval over which an observation point is sensitive to a given parameter depends on the actual values of the parameters in the underlying physical system.

Differential Roles of Thought Suppression and Dispositional Mindfulness in Posttraumatic Stress Symptoms and Craving

PubMed Central

Garland, Eric; Roberts-Lewis, Amelia

2012-01-01

Exposure to traumatic events often results in severe distress which may elicit self-medication behaviors. Yet, some individuals exposed to trauma do not develop post-traumatic stress symptoms and comorbid addictive impulses. In the wake of traumatic events, psychological processes like thought suppression and mindfulness may modulate post-traumatic stress and craving for substances. We examined the differential roles of mindfulness and suppression in comorbid post-traumatic stress and craving in a sample of 125 persons with extensive trauma histories and psychiatric symptoms in residential treatment for substance dependence. Results indicated that thought suppression, rather than extent of trauma history, significantly predicted post-traumatic stress symptom severity while dispositional mindfulness significantly predicted both post-traumatic stress symptoms and craving. In multiple regression models, mindfulness and thought suppression combined explained nearly half of the variance in post-traumatic stress symptoms and one-quarter of the variance in substance craving. Moreover, multivariate path analysis indicated that prior traumatic experience was associated with greater thought suppression, which in turn was correlated with increased post-traumatic stress symptoms and drug craving, whereas dispositional mindfulness was associated with decreased suppression, post-traumatic stress, and craving. The maladaptive strategy of thought suppression appears to be linked with adverse psychological consequences of traumatic life events. In contrast, dispositional mindfulness appears to be a protective factor that buffers individuals from experiencing more severe post-traumatic stress symptoms and craving. PMID:22385734

Prenatal maternal stress predicts autism traits in 6½ year-old children: Project Ice Storm.

PubMed

Walder, Deborah J; Laplante, David P; Sousa-Pires, Alexandra; Veru, Franz; Brunet, Alain; King, Suzanne

2014-10-30

Research implicates prenatal maternal stress (PNMS) as a risk factor for neurodevelopmental disorders; however few studies report PNMS effects on autism risk in offspring. We examined, prospectively, the degree to which objective and subjective elements of PNMS explained variance in autism-like traits among offspring, and tested moderating effects of sex and PNMS timing in utero. Subjects were 89 (46F/43M) children who were in utero during the 1998 Quebec Ice Storm. Soon after the storm, mothers completed questionnaires on objective exposure and subjective distress, and completed the Autism Spectrum Screening Questionnaire (ASSQ) for their children at age 6½. ASSQ scores were higher among boys than girls. Greater objective and subjective PNMS predicted higher ASSQ independent of potential confounds. An objective-by-subjective interaction suggested that when subjective PNMS was high, objective PNMS had little effect; whereas when subjective PNMS was low, objective PNMS strongly affected ASSQ scores. A timing-by-objective stress interaction suggested objective stress significantly affected ASSQ in first-trimester exposed children, though less so with later exposure. The final regression explained 43% of variance in ASSQ scores; the main effect of sex and the sex-by-PNMS interactions were not significant. Findings may help elucidate neurodevelopmental origins of non-clinical autism-like traits from a dimensional perspective. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Albumin and pre-albumin levels do not reflect the nutritional status of female adolescents with restrictive eating disorders.

PubMed

Huysentruyt, Koen; De Schepper, Jean; Vanbesien, Jesse; Vandenplas, Yvan

2016-04-01

Albumin and pre-albumin are frequently used as nutritional markers in clinical practice. We examined whether serum albumin and pre-albumin were predicted by body mass index (BMI), hydration and/or inflammation in female adolescents with a recently diagnosed restrictive eating disorder (RED). This was a retrospective study of female adolescents with RED from 2002 to 2011. Low albumin and pre-albumin levels were defined as <3.5 g/dL and <20 mg/dL, respectively. We assessed inflammation using the erythrocyte sedimentation rate (ESR) and dehydration using the haematocrit levels. We included 75 females with a mean age of 15.2 years and 64% had a BMI Z score of <-2. The mean albumin and pre-albumin levels were 4.8 g/dL and 22.2 mg/dL, respectively, with 24% of the children having low pre-albumin and none having low albumin levels. The stepwise multiple regression for albumin identified ESR and haematocrit as significant predictors, which explained 14.8% of the variance. Age was the only significant predictor for pre-albumin, which explained 15.3% of the variance. Albumin, but not pre-albumin, levels were primarily predicted by low-grade inflammation and hydration, but not by BMI. These markers should not be used to assess nutritional status in adolescents with RED. ©2015 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.

Crisis of Meaning Predicts Suicidality in Youth Independently of Depression.

PubMed

Schnell, Tatjana; Gerstner, Rebekka; Krampe, Henning

2018-02-23

At times, the question for meaning comes to nothing and a crisis of meaning ensues. This state is very painful, but difficult to account. Both those who suffer from it and care professionals find themselves at a loss for words. This study introduces an operationalization of a crisis of meaning. It aims to distinguish the concept from depression, and to investigate whether a crisis of meaning can explain suicidality beyond the known protective and risk factors self-esteem, family functioning, life-event load, and depression. Final-year school pupils in Ecuador (N = 300) completed questionnaires assessing the above variables. Data were analyzed using chi-square, hierarchic multiple regression, serial mediation, and moderator analyses. Crisis of meaning was distinguished from depression. It explained a significant amount of variance in suicidality beyond the mentioned protective and risk factors. For males, crisis of meaning was the only significant risk factor, and the strongest predictor overall. The acute risk factors depression and crisis of meaning mediated the effects of the baseline factors self-esteem, family functioning, and life-event load on suicidality. The study was cross-sectional; assessed factors predicted variance in suicidal thoughts, plans, and past suicide attempts, while their relevance cannot be generalized to actual future suicide attempts. A crisis of meaning is an important factor to take into account in further research on the prevention and treatment of people at risk of suicide.

Dissociation and psychosis in dissociative identity disorder and schizophrenia.

PubMed

Laddis, Andreas; Dell, Paul F

2012-01-01

Dissociative symptoms, first-rank symptoms of schizophrenia, and delusions were assessed in 40 schizophrenia patients and 40 dissociative identity disorder (DID) patients with the Multidimensional Inventory of Dissociation (MID). Schizophrenia patients were diagnosed with the Structured Clinical Interview for the DSM-IV Axis I Disorders; DID patients were diagnosed with the Structured Clinical Interview for DSM-IV Dissociative Disorders-Revised. DID patients obtained significantly (a) higher dissociation scores; (b) higher passive-influence scores (first-rank symptoms); and (c) higher scores on scales that measure child voices, angry voices, persecutory voices, voices arguing, and voices commenting. Schizophrenia patients obtained significantly higher delusion scores than did DID patients. What is odd is that the dissociation scores of schizophrenia patients were unrelated to their reports of childhood maltreatment. Multiple regression analyses indicated that 81% of the variance in DID patients' dissociation scores was predicted by the MID's Ego-Alien Experiences Scale, whereas 92% of the variance in schizophrenia patients' dissociation scores was predicted by the MID's Voices Scale. We propose that schizophrenia patients' responses to the MID do not index the same pathology as do the responses of DID patients. We argue that neither phenomenological definitions of dissociation nor the current generation of dissociation instruments (which are uniformly phenomenological in nature) can distinguish between the dissociative phenomena of DID and what we suspect are just the dissociation-like phenomena of schizophrenia.

Genomic Prediction Accounting for Residual Heteroskedasticity.

PubMed

Ou, Zhining; Tempelman, Robert J; Steibel, Juan P; Ernst, Catherine W; Bates, Ronald O; Bello, Nora M

2015-11-12

Whole-genome prediction (WGP) models that use single-nucleotide polymorphism marker information to predict genetic merit of animals and plants typically assume homogeneous residual variance. However, variability is often heterogeneous across agricultural production systems and may subsequently bias WGP-based inferences. This study extends classical WGP models based on normality, heavy-tailed specifications and variable selection to explicitly account for environmentally-driven residual heteroskedasticity under a hierarchical Bayesian mixed-models framework. WGP models assuming homogeneous or heterogeneous residual variances were fitted to training data generated under simulation scenarios reflecting a gradient of increasing heteroskedasticity. Model fit was based on pseudo-Bayes factors and also on prediction accuracy of genomic breeding values computed on a validation data subset one generation removed from the simulated training dataset. Homogeneous vs. heterogeneous residual variance WGP models were also fitted to two quantitative traits, namely 45-min postmortem carcass temperature and loin muscle pH, recorded in a swine resource population dataset prescreened for high and mild residual heteroskedasticity, respectively. Fit of competing WGP models was compared using pseudo-Bayes factors. Predictive ability, defined as the correlation between predicted and observed phenotypes in validation sets of a five-fold cross-validation was also computed. Heteroskedastic error WGP models showed improved model fit and enhanced prediction accuracy compared to homoskedastic error WGP models although the magnitude of the improvement was small (less than two percentage points net gain in prediction accuracy). Nevertheless, accounting for residual heteroskedasticity did improve accuracy of selection, especially on individuals of extreme genetic merit. Copyright © 2016 Ou et al.

Variance component and breeding value estimation for genetic heterogeneity of residual variance in Swedish Holstein dairy cattle.

PubMed

Rönnegård, L; Felleki, M; Fikse, W F; Mulder, H A; Strandberg, E

2013-04-01

Trait uniformity, or micro-environmental sensitivity, may be studied through individual differences in residual variance. These differences appear to be heritable, and the need exists, therefore, to fit models to predict breeding values explaining differences in residual variance. The aim of this paper is to estimate breeding values for micro-environmental sensitivity (vEBV) in milk yield and somatic cell score, and their associated variance components, on a large dairy cattle data set having more than 1.6 million records. Estimation of variance components, ordinary breeding values, and vEBV was performed using standard variance component estimation software (ASReml), applying the methodology for double hierarchical generalized linear models. Estimation using ASReml took less than 7 d on a Linux server. The genetic standard deviations for residual variance were 0.21 and 0.22 for somatic cell score and milk yield, respectively, which indicate moderate genetic variance for residual variance and imply that a standard deviation change in vEBV for one of these traits would alter the residual variance by 20%. This study shows that estimation of variance components, estimated breeding values and vEBV, is feasible for large dairy cattle data sets using standard variance component estimation software. The possibility to select for uniformity in Holstein dairy cattle based on these estimates is discussed. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A Signal to Noise Paradox in Climate Predictions

NASA Astrophysics Data System (ADS)

Eade, R.; Scaife, A. A.; Smith, D.; Dunstone, N. J.; MacLachlan, C.; Hermanson, L.; Ruth, C.

2017-12-01

Recent advances in climate modelling have resulted in the achievement of skilful long-range prediction, particular that associated with the winter circulation over the north Atlantic (e.g. Scaife et al 2014, Stockdale et al 2015, Dunstone et al 2016) including impacts over Europe and North America, and further afield. However, while highly significant and potentially useful skill exists, the signal-to-noise ratio of the ensemble mean to total variability in these ensemble predictions is anomalously small (Scaife et al 2014) and the correlation between the ensemble mean and historical observations exceeds the proportion of predictable variance in the ensemble (Eade et al 2014). This means the real world is more predictable than our climate models. Here we discuss a series of hypothesis tests that have been carried out to assess issues with model mechanisms compared to the observed world, and present the latest findings in our attempt to determine the cause of the anomalously weak predicted signals in our seasonal-to-decadal hindcasts.

The role of individualism and the Five-Factor Model in the prediction of performance in a leaderless group discussion.

PubMed

Waldman, David A; Atwater, Leanne E; Davidson, Ronald A

2004-02-01

Personality has seen a resurgence in the work performance literature. The Five-Factor Model (FFM) represents a set of personality factors that has received the most attention in recent years. Despite its popularity, the FFM may not be sufficiently comprehensive to account for relevant variation across performance dimensions or tasks. Accordingly, the present study also considers how individualism may predict additional variance in performance beyond the FFM. The study involved 152 undergraduate students who experienced a leaderless group discussion (LGD) exercise. Results showed that while the FFM accounted for variance in students' LGD performance, individualism (independence) accounted for additional, unique variance. Furthermore, analyses of the group compositions revealed curvilinear relationships between the relative amount of extraversion, conscientiousness, and individualism in relation to group-level performance.

Local sharpening and subspace wavefront correction with predictive dynamic digital holography

NASA Astrophysics Data System (ADS)

Sulaiman, Sennan; Gibson, Steve

2017-09-01

Digital holography holds several advantages over conventional imaging and wavefront sensing, chief among these being significantly fewer and simpler optical components and the retrieval of complex field. Consequently, many imaging and sensing applications including microscopy and optical tweezing have turned to using digital holography. A significant obstacle for digital holography in real-time applications, such as wavefront sensing for high energy laser systems and high speed imaging for target racking, is the fact that digital holography is computationally intensive; it requires iterative virtual wavefront propagation and hill-climbing to optimize some sharpness criteria. It has been shown recently that minimum-variance wavefront prediction can be integrated with digital holography and image sharpening to reduce significantly large number of costly sharpening iterations required to achieve near-optimal wavefront correction. This paper demonstrates further gains in computational efficiency with localized sharpening in conjunction with predictive dynamic digital holography for real-time applications. The method optimizes sharpness of local regions in a detector plane by parallel independent wavefront correction on reduced-dimension subspaces of the complex field in a spectral plane.

Linking precipitation, evapotranspiration and soil moisture content for the improvement of predictability over land

NASA Astrophysics Data System (ADS)

Catalano, Franco; Alessandri, Andrea; De Felice, Matteo

2013-04-01

Climate change scenarios are expected to show an intensification of the hydrological cycle together with modifications of evapotranspiration and soil moisture content. Evapotranspiration changes have been already evidenced for the end of the 20th century. The variance of evapotranspiration has been shown to be strongly related to the variance of precipitation over land. Nevertheless, the feedbacks between evapotranspiration, soil moisture and precipitation have not yet been completely understood at present-day. Furthermore, soil moisture reservoirs are associated to a memory and thus their proper initialization may have a strong influence on predictability. In particular, the linkage between precipitation and soil moisture is modulated by the effects on evapotranspiration. Therefore, the investigation of the coupling between these variables appear to be of primary importance for the improvement of predictability over the continents. The coupled manifold (CM) technique (Navarra and Tribbia 2005) is a method designed to separate the effects of the variability of two variables which are connected. This method has proved to be successful for the analysis of different climate fields, like precipitation, vegetation and sea surface temperature. In particular, the coupled variables reveal patterns that may be connected with specific phenomena, thus providing hints regarding potential predictability. In this study we applied the CM to recent observational datasets of precipitation (from CRU), evapotranspiration (from GIMMS and MODIS satellite-based estimates) and soil moisture content (from ESA) spanning a time period of 23 years (1984-2006) with a monthly frequency. Different data stratification (monthly, seasonal, summer JJA) have been employed to analyze the persistence of the patterns and their characteristical time scales and seasonality. The three variables considered show a significant coupling among each other. Interestingly, most of the signal of the evapotranspiration-precipitation coupled terms comes from the summer (JJA), when convective motions increase sensitivity to surface conditions over land. The CM analysis of the response of evapotranspiration to soil moisture allowed a characterization of the robustness of the coupling between these two variables which has been identified as a key requirement for precipitation predictability (Koster et al. 2000). References Navarra, A., and J. Tribbia (2005), The coupled manifold, J. Atmos. Sci., 62, 310-330. Koster, R. D., M. J. Suarez, and M. Heiser (2000), Variance and predictability of precipitation at seasonal-to-interannual timescales, J. Hydrometeor., 1, 26-46.

A method to estimate the contribution of regional genetic associations to complex traits from summary association statistics.

PubMed

Pare, Guillaume; Mao, Shihong; Deng, Wei Q

2016-06-08

Despite considerable efforts, known genetic associations only explain a small fraction of predicted heritability. Regional associations combine information from multiple contiguous genetic variants and can improve variance explained at established association loci. However, regional associations are not easily amenable to estimation using summary association statistics because of sensitivity to linkage disequilibrium (LD). We now propose a novel method, LD Adjusted Regional Genetic Variance (LARGV), to estimate phenotypic variance explained by regional associations using summary statistics while accounting for LD. Our method is asymptotically equivalent to a multiple linear regression model when no interaction or haplotype effects are present. It has several applications, such as ranking of genetic regions according to variance explained or comparison of variance explained by two or more regions. Using height and BMI data from the Health Retirement Study (N = 7,776), we show that most genetic variance lies in a small proportion of the genome and that previously identified linkage peaks have higher than expected regional variance.

A method to estimate the contribution of regional genetic associations to complex traits from summary association statistics

PubMed Central

Pare, Guillaume; Mao, Shihong; Deng, Wei Q.

2016-01-01

Despite considerable efforts, known genetic associations only explain a small fraction of predicted heritability. Regional associations combine information from multiple contiguous genetic variants and can improve variance explained at established association loci. However, regional associations are not easily amenable to estimation using summary association statistics because of sensitivity to linkage disequilibrium (LD). We now propose a novel method, LD Adjusted Regional Genetic Variance (LARGV), to estimate phenotypic variance explained by regional associations using summary statistics while accounting for LD. Our method is asymptotically equivalent to a multiple linear regression model when no interaction or haplotype effects are present. It has several applications, such as ranking of genetic regions according to variance explained or comparison of variance explained by two or more regions. Using height and BMI data from the Health Retirement Study (N = 7,776), we show that most genetic variance lies in a small proportion of the genome and that previously identified linkage peaks have higher than expected regional variance. PMID:27273519

Physical activity, but not sedentary time, influences bone strength in late adolescence.

PubMed

Tan, Vina Ps; Macdonald, Heather M; Gabel, Leigh; McKay, Heather A

2018-03-20

Physical activity is essential for optimal bone strength accrual, but we know little about interactions between physical activity, sedentary time, and bone outcomes in older adolescents. Physical activity (by accelerometer and self-report) positively predicted bone strength and the distal and midshaft tibia in 15-year-old boys and girls. Lean body mass mediated the relationship between physical activity and bone strength in adolescents. To examine the influence of physical activity (PA) and sedentary time on bone strength, structure, and density in older adolescents. We used peripheral quantitative computed tomography to estimate bone strength at the distal tibia (8% site; bone strength index, BSI) and tibial midshaft (50% site; polar strength strain index, SSI p ) in adolescent boys (n = 86; 15.3 ± 0.4 years) and girls (n = 106; 15.3 ± 0.4 years). Using accelerometers (GT1M, Actigraph), we measured moderate-to-vigorous PA (MVPA Accel ), vigorous PA (VPA Accel ), and sedentary time in addition to self-reported MVPA (MVPA PAQ-A ) and impact PA (ImpactPA PAQ-A ). We examined relations between PA and sedentary time and bone outcomes, adjusting for ethnicity, maturity, tibial length, and total body lean mass. At the distal tibia, MVPA Accel and VPA Accel positively predicted BSI (explained 6-7% of the variance, p < 0.05). After adjusting for lean mass, only VPA Accel explained residual variance in BSI. At the tibial midshaft, MVPA Accel , but not VPA Accel , positively predicted SSI p (explained 3% of the variance, p = 0.01). Lean mass attenuated this association. MVPA PAQ-A and ImpactPA PAQ-A also positively predicted BSI and SSI p (explained 2-4% of the variance, p < 0.05), but only ImpactPA PAQ-A explained residual variance in BSI after accounting for lean mass. Sedentary time did not independently predict bone strength at either site. Greater tibial bone strength in active adolescents is mediated, in part, by lean mass. Despite spending most of their day in sedentary pursuits, adolescents' bone strength was not negatively influenced by sedentary time.

Cross-Participant EEG-Based Assessment of Cognitive Workload Using Multi-Path Convolutional Recurrent Neural Networks.

PubMed

Hefron, Ryan; Borghetti, Brett; Schubert Kabban, Christine; Christensen, James; Estepp, Justin

2018-04-26

Applying deep learning methods to electroencephalograph (EEG) data for cognitive state assessment has yielded improvements over previous modeling methods. However, research focused on cross-participant cognitive workload modeling using these techniques is underrepresented. We study the problem of cross-participant state estimation in a non-stimulus-locked task environment, where a trained model is used to make workload estimates on a new participant who is not represented in the training set. Using experimental data from the Multi-Attribute Task Battery (MATB) environment, a variety of deep neural network models are evaluated in the trade-space of computational efficiency, model accuracy, variance and temporal specificity yielding three important contributions: (1) The performance of ensembles of individually-trained models is statistically indistinguishable from group-trained methods at most sequence lengths. These ensembles can be trained for a fraction of the computational cost compared to group-trained methods and enable simpler model updates. (2) While increasing temporal sequence length improves mean accuracy, it is not sufficient to overcome distributional dissimilarities between individuals’ EEG data, as it results in statistically significant increases in cross-participant variance. (3) Compared to all other networks evaluated, a novel convolutional-recurrent model using multi-path subnetworks and bi-directional, residual recurrent layers resulted in statistically significant increases in predictive accuracy and decreases in cross-participant variance.

Limits to behavioral evolution: the quantitative genetics of a complex trait under directional selection.

PubMed

Careau, Vincent; Wolak, Matthew E; Carter, Patrick A; Garland, Theodore

2013-11-01

Replicated selection experiments provide a powerful way to study how "multiple adaptive solutions" may lead to differences in the quantitative-genetic architecture of selected traits and whether this may translate into differences in the timing at which evolutionary limits are reached. We analyze data from 31 generations (n=17,988) of selection on voluntary wheel running in house mice. The rate of initial response, timing of selection limit, and height of the plateau varied significantly between sexes and among the four selected lines. Analyses of litter size and realized selection differentials seem to rule out counterposing natural selection as a cause of the selection limits. Animal-model analyses showed that although the additive genetic variance was significantly lower in selected than control lines, both before and after the limits, the decrease was not sufficient to explain the limits. Moreover, directional selection promoted a negative covariance between additive and maternal genetic variance over the first 10 generations. These results stress the importance of replication in selection studies of higher-level traits and highlight the fact that long-term predictions of response to selection are not necessarily expected to be linear because of the variable effects of selection on additive genetic variance and maternal effects. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.

Female scarcity reduces women's marital ages and increases variance in men's marital ages.

PubMed

Kruger, Daniel J; Fitzgerald, Carey J; Peterson, Tom

2010-08-05

When women are scarce in a population relative to men, they have greater bargaining power in romantic relationships and thus may be able to secure male commitment at earlier ages. Male motivation for long-term relationship commitment may also be higher, in conjunction with the motivation to secure a prospective partner before another male retains her. However, men may also need to acquire greater social status and resources to be considered marriageable. This could increase the variance in male marital age, as well as the average male marital age. We calculated the Operational Sex Ratio, and means, medians, and standard deviations in marital ages for women and men for the 50 largest Metropolitan Statistical Areas in the United States with 2000 U.S Census data. As predicted, where women are scarce they marry earlier on average. However, there was no significant relationship with mean male marital ages. The variance in male marital age increased with higher female scarcity, contrasting with a non-significant inverse trend for female marital age variation. These findings advance the understanding of the relationship between the OSR and marital patterns. We believe that these results are best accounted for by sex specific attributes of reproductive value and associated mate selection criteria, demonstrating the power of an evolutionary framework for understanding human relationships and demographic patterns.

Cross-Participant EEG-Based Assessment of Cognitive Workload Using Multi-Path Convolutional Recurrent Neural Networks

PubMed Central

Hefron, Ryan; Borghetti, Brett; Schubert Kabban, Christine; Christensen, James; Estepp, Justin

2018-01-01

Applying deep learning methods to electroencephalograph (EEG) data for cognitive state assessment has yielded improvements over previous modeling methods. However, research focused on cross-participant cognitive workload modeling using these techniques is underrepresented. We study the problem of cross-participant state estimation in a non-stimulus-locked task environment, where a trained model is used to make workload estimates on a new participant who is not represented in the training set. Using experimental data from the Multi-Attribute Task Battery (MATB) environment, a variety of deep neural network models are evaluated in the trade-space of computational efficiency, model accuracy, variance and temporal specificity yielding three important contributions: (1) The performance of ensembles of individually-trained models is statistically indistinguishable from group-trained methods at most sequence lengths. These ensembles can be trained for a fraction of the computational cost compared to group-trained methods and enable simpler model updates. (2) While increasing temporal sequence length improves mean accuracy, it is not sufficient to overcome distributional dissimilarities between individuals’ EEG data, as it results in statistically significant increases in cross-participant variance. (3) Compared to all other networks evaluated, a novel convolutional-recurrent model using multi-path subnetworks and bi-directional, residual recurrent layers resulted in statistically significant increases in predictive accuracy and decreases in cross-participant variance. PMID:29701668

Association of comorbid mental health symptoms and physical health conditions with employee productivity.

PubMed

Parker, Kristin M; Wilson, Mark G; Vandenberg, Robert J; DeJoy, David M; Orpinas, Pamela

2009-10-01

This study tests the hypothesis that employees with comorbid physical health conditions and mental health symptoms are less productive than other employees. Self-reported health status and productivity measures were collected from 1723 employees of a national retail organization. chi2, analysis of variance, and linear contrast analyses were conducted to evaluate whether health status groups differed on productivity measures. Multivariate linear regression and multinomial logistic regression analyses were conducted to analyze how predictive health status was of productivity. Those with comorbidities were significantly less productive on all productivity measures compared with all other health status groups and those with only physical health conditions or mental health symptoms. Health status also significantly predicted levels of employee productivity. These findings provide evidence for the relationship between health statuses and productivity, which has potential programmatic implications.

Relationship of physical activity to fundamental movement skills among adolescents.

PubMed

Okely, A D; Booth, M L; Patterson, J W

2001-11-01

To determine the relationship of participation in organized and nonorganized physical activity with fundamental movement skills among adolescents. Male and female children in Grade 8 (mean age, 13.3 yr) and Grade 10 (mean age, 15.3 yr) were assessed on six fundamental movement skills (run, vertical jump, catch, overhand throw, forehand strike, and kick). Physical activity was assessed using a self-report recall measure where students reported the type, duration, and frequency of participation in organized physical activity and nonorganized physical activity during a usual week. Multiple regression analysis indicated that fundamental movement skills significantly predicted time in organized physical activity, although the percentage of variance it could explain was small. This prediction was stronger for girls than for boys. Multiple regression analysis showed no relationship between time in nonorganized physical activity and fundamental movement skills. Fundamental movement skills are significantly associated with adolescents' participation in organized physical activity, but predict only a small portion of it.

A fractional factorial probabilistic collocation method for uncertainty propagation of hydrologic model parameters in a reduced dimensional space

NASA Astrophysics Data System (ADS)

Wang, S.; Huang, G. H.; Huang, W.; Fan, Y. R.; Li, Z.

2015-10-01

In this study, a fractional factorial probabilistic collocation method is proposed to reveal statistical significance of hydrologic model parameters and their multi-level interactions affecting model outputs, facilitating uncertainty propagation in a reduced dimensional space. The proposed methodology is applied to the Xiangxi River watershed in China to demonstrate its validity and applicability, as well as its capability of revealing complex and dynamic parameter interactions. A set of reduced polynomial chaos expansions (PCEs) only with statistically significant terms can be obtained based on the results of factorial analysis of variance (ANOVA), achieving a reduction of uncertainty in hydrologic predictions. The predictive performance of reduced PCEs is verified by comparing against standard PCEs and the Monte Carlo with Latin hypercube sampling (MC-LHS) method in terms of reliability, sharpness, and Nash-Sutcliffe efficiency (NSE). Results reveal that the reduced PCEs are able to capture hydrologic behaviors of the Xiangxi River watershed, and they are efficient functional representations for propagating uncertainties in hydrologic predictions.

Genome-Wide Polygenic Scores Predict Reading Performance Throughout the School Years.

PubMed

Selzam, Saskia; Dale, Philip S; Wagner, Richard K; DeFries, John C; Cederlöf, Martin; O'Reilly, Paul F; Krapohl, Eva; Plomin, Robert

2017-07-04

It is now possible to create individual-specific genetic scores, called genome-wide polygenic scores (GPS). We used a GPS for years of education ( EduYears ) to predict reading performance assessed at UK National Curriculum Key Stages 1 (age 7), 2 (age 12) and 3 (age 14) and on reading tests administered at ages 7 and 12 in a UK sample of 5,825 unrelated individuals. EduYears GPS accounts for up to 5% of the variance in reading performance at age 14. GPS predictions remained significant after accounting for general cognitive ability and family socioeconomic status. Reading performance of children in the lowest and highest 12.5% of the EduYears GPS distribution differed by a mean growth in reading ability of approximately two school years. It seems certain that polygenic scores will be used to predict strengths and weaknesses in education.

Conceptualizing and measuring illness self-concept: a comparison with self-esteem and optimism in predicting fibromyalgia adjustment.

PubMed

Morea, Jessica M; Friend, Ronald; Bennett, Robert M

2008-12-01

Illness self-concept (ISC), or the extent to which individuals are consumed by their illness, was theoretically described and evaluated with the Illness Self-Concept Scale (ISCS), a new 23-item scale, to predict adjustment in fibromyalgia. To establish convergent and discriminant validity, illness self-concept was compared to self-esteem and optimism in predicting health status, illness intrusiveness, depression, and life satisfaction. The ISCS demonstrated good reliability (alpha = .94; test-retest r = .80) and was a strong predictor of outcomes, even after controlling for optimism or self-esteem. The ISCS predicted unique variance in health-related outcomes; optimism and self-esteem did not, providing construct validation. Illness self-concept may play a significant role in coping with fibromyalgia and may prove useful in the evaluation of other chronic illnesses. (c) 2008 Wiley Periodicals, Inc.

Prosociality: the contribution of traits, values, and self-efficacy beliefs.

PubMed

Caprara, Gian Vittorio; Alessandri, Guido; Eisenberg, Nancy

2012-06-01

The present study examined how agreeableness, self-transcendence values, and empathic self-efficacy beliefs predict individuals' tendencies to engage in prosocial behavior (i.e., prosociality) across time. Participants were 340 young adults, 190 women and 150 men, age approximately 21 years at Time 1 and 25 years at Time 2. Measures of agreeableness, self-transcendence, empathic self-efficacy beliefs, and prosociality were collected at 2 time points. The findings corroborated the posited paths of relations, with agreeableness directly predicting self-transcendence and indirectly predicting empathic self-efficacy beliefs and prosociality. Self-transcendence mediated the relation between agreeableness and empathic self-efficacy beliefs. Empathic self-efficacy beliefs mediated the relation of agreeableness and self-transcendence to prosociality. Finally, earlier prosociality predicted agreeableness and empathic self-efficacy beliefs assessed at Time 2. The posited conceptual model accounted for a significant portion of variance in prosociality and provides guidance to interventions aimed at promoting prosociality. 2012 APA, all rights reserved

Persistent grief in the aftermath of mass violence: the predictive roles of posttraumatic stress symptoms, self-efficacy, and disrupted worldview.

PubMed

Smith, Andrew J; Abeyta, Andrew A; Hughes, Michael; Jones, Russell T

2015-03-01

This study tested a conceptual model merging anxiety buffer disruption and social-cognitive theories to predict persistent grief severity among students who lost a close friend, significant other, and/or professor/teacher in tragic university campus shootings. A regression-based path model tested posttraumatic stress (PTS) symptom severity 3 to 4 months postshooting (Time 1) as a predictor of grief severity 1 year postshootings (Time 2), both directly and indirectly through cognitive processes (self-efficacy and disrupted worldview). Results revealed a model that predicted 61% of the variance in Time 2 grief severity. Hypotheses were supported, demonstrating that Time 1 PTS severity indirectly, positively predicted Time 2 grief severity through undermining self-efficacy and more severely disrupting worldview. Findings and theoretical interpretation yield important insights for future research and clinical application. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Brain Activity in Self- and Value-Related Regions in Response to Online Antismoking Messages Predicts Behavior Change

PubMed Central

Cooper, Nicole; Tompson, Steve; O’Donnell, Matthew Brook; Falk, Emily B.

2017-01-01

In this study, we combined approaches from media psychology and neuroscience to ask whether brain activity in response to online antismoking messages can predict smoking behavior change. In particular, we examined activity in subregions of the medial prefrontal cortex linked to self- and value-related processing, to test whether these neurocognitive processes play a role in message-consistent behavior change. We observed significant relationships between activity in both brain regions of interest and behavior change (such that higher activity predicted a larger reduction in smoking). Furthermore, activity in these brain regions predicted variance independent of traditional, theory-driven self-report metrics such as intention, self-efficacy, and risk perceptions. We propose that valuation is an additional cognitive process that should be investigated further as we search for a mechanistic explanation of the relationship between brain activity and media effects relevant to health behavior change. PMID:29057013

Genome-Wide Polygenic Scores Predict Reading Performance Throughout the School Years

PubMed Central

Selzam, Saskia; Dale, Philip S.; Wagner, Richard K.; DeFries, John C.; Cederlöf, Martin; O’Reilly, Paul F.; Krapohl, Eva; Plomin, Robert

2017-01-01

ABSTRACT It is now possible to create individual-specific genetic scores, called genome-wide polygenic scores (GPS). We used a GPS for years of education (EduYears) to predict reading performance assessed at UK National Curriculum Key Stages 1 (age 7), 2 (age 12) and 3 (age 14) and on reading tests administered at ages 7 and 12 in a UK sample of 5,825 unrelated individuals. EduYears GPS accounts for up to 5% of the variance in reading performance at age 14. GPS predictions remained significant after accounting for general cognitive ability and family socioeconomic status. Reading performance of children in the lowest and highest 12.5% of the EduYears GPS distribution differed by a mean growth in reading ability of approximately two school years. It seems certain that polygenic scores will be used to predict strengths and weaknesses in education. PMID:28706435

Predictive Utility of Personality Disorder in Depression: Comparison of Outcomes and Taxonomic Approach.

PubMed

Newton-Howes, Giles; Mulder, Roger; Ellis, Pete M; Boden, Joseph M; Joyce, Peter

2017-09-19

There is debate around the best model for diagnosing personality disorder, both in terms of its relationship to the empirical data and clinical utility. Four randomized controlled trials examining various treatments for depression were analyzed at an individual patient level. Three different approaches to the diagnosis of personality disorder were analyzed in these patients. A total of 578 depressed patients were included in the analysis. Personality disorder, however measured, was of little predictive utility in the short term but added significantly to predictive modelling of medium-term outcomes, accounting for more than twice as much of the variance in social functioning outcome as depression psychopathology. Personality disorder assessment is of predictive utility with longer timeframes and when considering social outcomes as opposed to symptom counts. This utility is sufficiently great that there appears to be value in assessing personality; however, no particular approach outperforms any other.

Predicting dynamic knee joint load with clinical measures in people with medial knee osteoarthritis.

PubMed

Hunt, Michael A; Bennell, Kim L

2011-08-01

Knee joint loading, as measured by the knee adduction moment (KAM), has been implicated in the pathogenesis of knee osteoarthritis (OA). Given that the KAM can only currently be accurately measured in the laboratory setting with sophisticated and expensive equipment, its utility in the clinical setting is limited. This study aimed to determine the ability of a combination of four clinical measures to predict KAM values. Three-dimensional motion analysis was used to calculate the peak KAM at a self-selected walking speed in 47 consecutive individuals with medial compartment knee OA and varus malalignment. Clinical predictors included: body mass; tibial angle measured using an inclinometer; walking speed; and visually observed trunk lean toward the affected limb during the stance phase of walking. Multiple linear regression was performed to predict KAM magnitudes using the four clinical measures. A regression model including body mass (41% explained variance), tibial angle (17% explained variance), and walking speed (9% explained variance) explained a total of 67% of variance in the peak KAM. Our study demonstrates that a set of measures easily obtained in the clinical setting (body mass, tibial alignment, and walking speed) can help predict the KAM in people with medial knee OA. Identifying those patients who are more likely to experience high medial knee loads could assist clinicians in deciding whether load-modifying interventions may be appropriate for patients, whilst repeated assessment of joint load could provide a mechanism to monitor disease progression or success of treatment. Copyright © 2010 Elsevier B.V. All rights reserved.

Abbreviated neuropsychological assessment in schizophrenia

PubMed Central

Harvey, Philip D.; Keefe, Richard S. E.; Patterson, Thomas L.; Heaton, Robert K.; Bowie, Christopher R.

2008-01-01

The aim of this study was to identify the best subset of neuropsychological tests for prediction of several different aspects of functioning in a large (n = 236) sample of older people with schizophrenia. While the validity of abbreviated assessment methods has been examined before, there has never been a comparative study of the prediction of different elements of cognitive impairment, real-world outcomes, and performance-based measures of functional capacity. Scores on 10 different tests from a neuropsychological assessment battery were used to predict global neuropsychological (NP) performance (indexed with averaged scores or calculated general deficit scores), performance-based indices of everyday-living skills and social competence, and case-manager ratings of real-world functioning. Forward entry stepwise regression analyses were used to identify the best predictors for each of the outcomes measures. Then, the analyses were adjusted for estimated premorbid IQ, which reduced the magnitude, but not the structure, of the correlations. Substantial amounts (over 70%) of the variance in overall NP performance were accounted for by a limited number of NP tests. Considerable variance in measures of functional capacity was also accounted for by a limited number of tests. Different tests constituted the best predictor set for each outcome measure. A substantial proportion of the variance in several different NP and functional outcomes can be accounted for by a small number of NP tests that can be completed in a few minutes, although there is considerable unexplained variance. However, the abbreviated assessments that best predict different outcomes vary across outcomes. Future studies should determine whether responses to pharmacological and remediation treatments can be captured with brief assessments as well. PMID:18720182

A model of prediction and cross-validation of fat-free mass in men with motor complete spinal cord injury.

PubMed

Gorgey, Ashraf S; Dolbow, David R; Gater, David R

2012-07-01

To establish and validate prediction equations by using body weight to predict legs, trunk, and whole-body fat-free mass (FFM) in men with chronic complete spinal cord injury (SCI). Cross-sectional design. Research setting in a large medical center. Individuals with SCI (N=63) divided into prediction (n=42) and cross-validation (n=21) groups. Not applicable. Whole-body FFM and regional FFM were determined by using dual-energy x-ray absorptiometry. Body weight was measured by using a wheelchair weighing scale after subtracting the weight of the chair. Body weight predicted legs FFM (legs FFM=.09×body weight+6.1; R(2)=.25, standard error of the estimate [SEE]=3.1kg, P<.01), trunk FFM (trunk FFM=.21×body weight+8.6; R(2)=.56, SEE=3.6kg, P<.0001), and whole-body FFM (whole-body FFM=.288×body weight+26.3; R(2)=.53, SEE=5.3kg, P<.0001). The whole-body FFM(predicted) (FFM predicted from the derived equations) shared 86% of the variance in whole-body FFM(measured) (FFM measured using dual-energy x-ray absorptiometry scan) (R(2)=.86, SEE=1.8kg, P<.0001), 69% of trunk FFM(measured), and 66% of legs FFM(measured). The trunk FFM(predicted) shared 69% of the variance in trunk FFM(measured) (R(2)=.69, SEE=2.7kg, P<.0001), and legs FFM(predicted) shared 67% of the variance in legs FFM(measured) (R(2)=.67, SEE=2.8kg, P<.0001). Values of FFM did not differ between the prediction and validation groups. Body weight can be used to predict whole-body FFM and regional FFM. The predicted whole-body FFM improved the prediction of trunk FFM and legs FFM. Copyright © 2012 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Observed impacts of duration and seasonality of atmospheric-river landfalls on soil moisture and runoff in coastal northern California

USGS Publications Warehouse

Ralph, F.M.; Coleman, T.; Neiman, P.J.; Zamora, R.J.; Dettinger, Mike

2013-01-01

This study is motivated by diverse needs for better forecasts of extreme precipitation and floods. It is enabled by unique hourly observations collected over six years near California’s Russian River and by recent advances in the science of atmospheric rivers (ARs). This study fills key gaps limiting the prediction of ARs and, especially, their impacts by quantifying the duration of AR conditions and the role of duration in modulating hydrometeorological impacts. Precursor soil moisture conditions and their relationship to streamflow are also shown. On the basis of 91 well-observed events during 2004-10, the study shows that the passage of ARs over a coastal site lasted 20 h on average and that 12% of the AR events exceeded 30 h. Differences in storm-total water vapor transport directed up the mountain slope contribute 74% of the variance in storm-total rainfall across the events and 61% of the variance in storm-total runoff volume. ARs with double the composite mean duration produced nearly 6 times greater peak streamflow and more than 7 times the storm-total runoff volume. When precursor soil moisture was less than 20%, even heavy rainfall did not lead to significant streamflow. Predicting which AR events are likely to produce extreme impacts on precipitation and runoff requires accurate prediction of AR duration at landfall and observations of precursor soil moisture conditions.

Job compensable factors and factor weights derived from job analysis data.

PubMed

Chi, Chia-Fen; Chang, Tin-Chang; Hsia, Ping-Ling; Song, Jen-Chieh

2007-06-01

Government data on 1,039 job titles in Taiwan were analyzed to assess possible relationships between job attributes and compensation. For each job title, 79 specific variables in six major classes (required education and experience, aptitude, interest, work temperament, physical demands, task environment) were coded to derive the statistical predictors of wage for managers, professionals, technical, clerical, service, farm, craft, operatives, and other workers. Of the 79 variables, only 23 significantly related to pay rate were subjected to a factor and multiple regression analysis for predicting monthly wages. Given the heterogeneous nature of collected job titles, a 4-factor solution (occupational knowledge and skills, human relations skills, work schedule hardships, physical hardships) explaining 43.8% of the total variance but predicting only 23.7% of the monthly pay rate was derived. On the other hand, multiple regression with 9 job analysis items (required education, professional training, professional certificate, professional experience, coordinating, leadership and directing, demand on hearing, proportion of shift working indoors, outdoors and others, rotating shift) better predicted pay and explained 32.5% of the variance. A direct comparison of factors and subfactors of job evaluation plans indicated mental effort and responsibility (accountability) had not been measured with the current job analysis data. Cross-validation of job evaluation factors and ratings with the wage rates is required to calibrate both.

Genomic prediction using preselected DNA variants from a GWAS with whole-genome sequence data in Holstein-Friesian cattle.

PubMed

Veerkamp, Roel F; Bouwman, Aniek C; Schrooten, Chris; Calus, Mario P L

2016-12-01

Whole-genome sequence data is expected to capture genetic variation more completely than common genotyping panels. Our objective was to compare the proportion of variance explained and the accuracy of genomic prediction by using imputed sequence data or preselected SNPs from a genome-wide association study (GWAS) with imputed whole-genome sequence data. Phenotypes were available for 5503 Holstein-Friesian bulls. Genotypes were imputed up to whole-genome sequence (13,789,029 segregating DNA variants) by using run 4 of the 1000 bull genomes project. The program GCTA was used to perform GWAS for protein yield (PY), somatic cell score (SCS) and interval from first to last insemination (IFL). From the GWAS, subsets of variants were selected and genomic relationship matrices (GRM) were used to estimate the variance explained in 2087 validation animals and to evaluate the genomic prediction ability. Finally, two GRM were fitted together in several models to evaluate the effect of selected variants that were in competition with all the other variants. The GRM based on full sequence data explained only marginally more genetic variation than that based on common SNP panels: for PY, SCS and IFL, genomic heritability improved from 0.81 to 0.83, 0.83 to 0.87 and 0.69 to 0.72, respectively. Sequence data also helped to identify more variants linked to quantitative trait loci and resulted in clearer GWAS peaks across the genome. The proportion of total variance explained by the selected variants combined in a GRM was considerably smaller than that explained by all variants (less than 0.31 for all traits). When selected variants were used, accuracy of genomic predictions decreased and bias increased. Although 35 to 42 variants were detected that together explained 13 to 19% of the total variance (18 to 23% of the genetic variance) when fitted alone, there was no advantage in using dense sequence information for genomic prediction in the Holstein data used in our study. Detection and selection of variants within a single breed are difficult due to long-range linkage disequilibrium. Stringent selection of variants resulted in more biased genomic predictions, although this might be due to the training population being the same dataset from which the selected variants were identified.

Multiple Domains of Parental Secure Base Support During Childhood and Adolescence Contribute to Adolescents’ Representations of Attachment as a Secure Base Script

PubMed Central

Vaughn, Brian E.; Waters, Theodore E. A.; Steele, Ryan D.; Roisman, Glenn I.; Bost, Kelly K.; Truitt, Warren; Waters, Harriet S.; Booth-LaForce, Cathryn

2016-01-01

Although attachment theory claims that early attachment representations reflecting the quality of the child’s “lived experiences” are maintained across developmental transitions, evidence that has emerged over the last decade suggests that the association between early relationship quality and adolescents’ attachment representations is fairly modest in magnitude. We used aspects of parenting beyond sensitivity over childhood and adolescence and early security to predict adolescents’ scripted attachment representations. At age 18 years, 673 participants from the NICHD Study of Early Child Care and Youth Development (SECCYD) completed the Attachment Script Assessment (ASA) from which we derived an assessment of secure base script knowledge. Measures of secure base support from childhood through age 15 years (e.g., parental monitoring of child activity, father presence in the home) were selected as predictors and accounted for an additional 8% of the variance in secure base script knowledge scores above and beyond direct observations of sensitivity and early attachment status alone, suggesting that adolescents’ scripted attachment representations reflect multiple domains of parenting. Cognitive and demographic variables also significantly increased predicted variance in secure base script knowledge by 2% each. PMID:27032953

Assimilation of seasonal chlorophyll and nutrient data into an adjoint three-dimensional ocean carbon cycle model: Sensitivity analysis and ecosystem parameter optimization

NASA Astrophysics Data System (ADS)

Tjiputra, Jerry F.; Polzin, Dierk; Winguth, Arne M. E.

2007-03-01

An adjoint method is applied to a three-dimensional global ocean biogeochemical cycle model to optimize the ecosystem parameters on the basis of SeaWiFS surface chlorophyll observation. We showed with identical twin experiments that the model simulated chlorophyll concentration is sensitive to perturbation of phytoplankton and zooplankton exudation, herbivore egestion as fecal pellets, zooplankton grazing, and the assimilation efficiency parameters. The assimilation of SeaWiFS chlorophyll data significantly improved the prediction of chlorophyll concentration, especially in the high-latitude regions. Experiments that considered regional variations of parameters yielded a high seasonal variance of ecosystem parameters in the high latitudes, but a low variance in the tropical regions. These experiments indicate that the adjoint model is, despite the many uncertainties, generally capable to optimize sensitive parameters and carbon fluxes in the euphotic zone. The best fit regional parameters predict a global net primary production of 36 Pg C yr-1, which lies within the range suggested by Antoine et al. (1996). Additional constraints of nutrient data from the World Ocean Atlas showed further reduction in the model-data misfit and that assimilation with extensive data sets is necessary.

Inducing Tropical Cyclones to Undergo Brownian Motion

NASA Astrophysics Data System (ADS)

Hodyss, D.; McLay, J.; Moskaitis, J.; Serra, E.

2014-12-01

Stochastic parameterization has become commonplace in numerical weather prediction (NWP) models used for probabilistic prediction. Here, a specific stochastic parameterization will be related to the theory of stochastic differential equations and shown to be affected strongly by the choice of stochastic calculus. From an NWP perspective our focus will be on ameliorating a common trait of the ensemble distributions of tropical cyclone (TC) tracks (or position), namely that they generally contain a bias and an underestimate of the variance. With this trait in mind we present a stochastic track variance inflation parameterization. This parameterization makes use of a properly constructed stochastic advection term that follows a TC and induces its position to undergo Brownian motion. A central characteristic of Brownian motion is that its variance increases with time, which allows for an effective inflation of an ensemble's TC track variance. Using this stochastic parameterization we present a comparison of the behavior of TCs from the perspective of the stochastic calculi of Itô and Stratonovich within an operational NWP model. The central difference between these two perspectives as pertains to TCs is shown to be properly predicted by the stochastic calculus and the Itô correction. In the cases presented here these differences will manifest as overly intense TCs, which, depending on the strength of the forcing, could lead to problems with numerical stability and physical realism.

Can Twitter be used to predict county excessive alcohol consumption rates?

PubMed Central

Ashford, Robert D.; Hemmons, Jessie; Summers, Dan; Hamilton, Casey

2018-01-01

Objectives The current study analyzes a large set of Twitter data from 1,384 US counties to determine whether excessive alcohol consumption rates can be predicted by the words being posted from each county. Methods Data from over 138 million county-level tweets were analyzed using predictive modeling, differential language analysis, and mediating language analysis. Results Twitter language data captures cross-sectional patterns of excessive alcohol consumption beyond that of sociodemographic factors (e.g. age, gender, race, income, education), and can be used to accurately predict rates of excessive alcohol consumption. Additionally, mediation analysis found that Twitter topics (e.g. ‘ready gettin leave’) can explain much of the variance associated between socioeconomics and excessive alcohol consumption. Conclusions Twitter data can be used to predict public health concerns such as excessive drinking. Using mediation analysis in conjunction with predictive modeling allows for a high portion of the variance associated with socioeconomic status to be explained. PMID:29617408

The Contribution of Agreeableness and Self-efficacy Beliefs to Prosociality

PubMed Central

CAPRARA, GIAN VITTORIO; ALESSANDRI, GUIDO; DI GIUNTA, LAURA; PANERAI, LAURA; EISENBERG, NANCY

2010-01-01

The present study examined how agreeableness and self-efficacy beliefs about responding empathically to others’ needs predict individuals’ prosociality across time. Participants were 377 adolescents (66% males) aged 16 at Time 1 and 18 at Time 2 who took part at this study. Measures of agreeableness, empathic self-efficacy and prosociality were collected at two time points. The findings corroborated the posited paths of relations to assigning agreeableness a major role in predicting the level of individuals’ prosociality. Empathic self-efficacy beliefs partially mediated the relation of agreeableness to prosociality. The posited conceptual model accounted for a significant portion of variance in prosociality and provides guidance with respect to interventions aimed at promoting prosociality. PMID:20592954

Physical controls on total and methylmercury concentrations in streams and lakes of the northeastern USA

USGS Publications Warehouse

Shanley, J.B.; Kamman, N.C.; Clair, T.A.; Chalmers, A.

2005-01-01

The physical factors controlling total mercury (HgT) and methylmercury (MeHg) concentrations in lakes and streams of northeastern USA were assessed in a regional data set containing 693 HgT and 385 corresponding MeHg concentrations in surface waters. Multiple regression models using watershed characteristics and climatic variables explained 38% or less of the variance in HgT and MeHg. Land cover percentages and soil permeability generally provided modest predictive power. Percent wetlands alone explained 19% of the variance in MeHg in streams at low-flow, and it was the only significant (p < 0.02) predictor for MeHg in lakes, albeit explaining only 7% of the variance. When stream discharge was added as a variable it became the dominant predictor for HgT in streams, improving the model r 2 from 0.19 to 0.38. Stream discharge improved the MeHg model more modestly, from r 2 of 0.25 to 0.33. Methylation efficiency (MeHg/HgT) was modeled well (r 2 of 0.78) when a seasonal term was incorporated (sine wave with annual period). Physical models explained 18% of the variance in fish Hg concentrations in 134 lakes and 55% in 20 reservoirs. Our results highlight the important role of seasonality and short-term hydrologic changes to the delivery of Hg to water bodies. ?? 2005 Springer Science+Business Media, Inc.

Validity of Bioelectrical Impedance Analysis to Estimation Fat-Free Mass in the Army Cadets.

PubMed

Langer, Raquel D; Borges, Juliano H; Pascoa, Mauro A; Cirolini, Vagner X; Guerra-Júnior, Gil; Gonçalves, Ezequiel M

2016-03-11

Bioelectrical Impedance Analysis (BIA) is a fast, practical, non-invasive, and frequently used method for fat-free mass (FFM) estimation. The aims of this study were to validate predictive equations of BIA to FFM estimation in Army cadets and to develop and validate a specific BIA equation for this population. A total of 396 males, Brazilian Army cadets, aged 17-24 years were included. The study used eight published predictive BIA equations, a specific equation in FFM estimation, and dual-energy X-ray absorptiometry (DXA) as a reference method. Student's t-test (for paired sample), linear regression analysis, and Bland-Altman method were used to test the validity of the BIA equations. Predictive BIA equations showed significant differences in FFM compared to DXA (p < 0.05) and large limits of agreement by Bland-Altman. Predictive BIA equations explained 68% to 88% of FFM variance. Specific BIA equations showed no significant differences in FFM, compared to DXA values. Published BIA predictive equations showed poor accuracy in this sample. The specific BIA equations, developed in this study, demonstrated validity for this sample, although should be used with caution in samples with a large range of FFM.

Ensemble projections of wildfire activity and carbonaceous aerosol concentrations over the western United States in the mid-21st century

PubMed Central

Yue, Xu; Mickley, Loretta J.; Logan, Jennifer A.; Kaplan, Jed O.

2013-01-01

We estimate future wildfire activity over the western United States during the mid-21st century (2046–2065), based on results from 15 climate models following the A1B scenario. We develop fire prediction models by regressing meteorological variables from the current and previous years together with fire indexes onto observed regional area burned. The regressions explain 0.25–0.60 of the variance in observed annual area burned during 1980–2004, depending on the ecoregion. We also parameterize daily area burned with temperature, precipitation, and relative humidity. This approach explains ~0.5 of the variance in observed area burned over forest ecoregions but shows no predictive capability in the semi-arid regions of Nevada and California. By applying the meteorological fields from 15 climate models to our fire prediction models, we quantify the robustness of our wildfire projections at mid-century. We calculate increases of 24–124% in area burned using regressions and 63–169% with the parameterization. Our projections are most robust in the southwestern desert, where all GCMs predict significant (p<0.05) meteorological changes. For forested ecoregions, more GCMs predict significant increases in future area burned with the parameterization than with the regressions, because the latter approach is sensitive to hydrological variables that show large inter-model variability in the climate projections. The parameterization predicts that the fire season lengthens by 23 days in the warmer and drier climate at mid-century. Using a chemical transport model, we find that wildfire emissions will increase summertime surface organic carbon aerosol over the western United States by 46–70% and black carbon by 20–27% at midcentury, relative to the present day. The pollution is most enhanced during extreme episodes: above the 84th percentile of concentrations, OC increases by ~90% and BC by ~50%, while visibility decreases from 130 km to 100 km in 32 Federal Class 1 areas in Rocky Mountains Forest. PMID:24015109

Branch xylem density variations across the Amazon Basin

NASA Astrophysics Data System (ADS)

Patiño, S.; Lloyd, J.; Paiva, R.; Baker, T. R.; Quesada, C. A.; Mercado, L. M.; Schmerler, J.; Schwarz, M.; Santos, A. J. B.; Aguilar, A.; Czimczik, C. I.; Gallo, J.; Horna, V.; Hoyos, E. J.; Jimenez, E. M.; Palomino, W.; Peacock, J.; Peña-Cruz, A.; Sarmiento, C.; Sota, A.; Turriago, J. D.; Villanueva, B.; Vitzthum, P.; Alvarez, E.; Arroyo, L.; Baraloto, C.; Bonal, D.; Chave, J.; Costa, A. C. L.; Herrera, R.; Higuchi, N.; Killeen, T.; Leal, E.; Luizão, F.; Meir, P.; Monteagudo, A.; Neil, D.; Núñez-Vargas, P.; Peñuela, M. C.; Pitman, N.; Priante Filho, N.; Prieto, A.; Panfil, S. N.; Rudas, A.; Salomão, R.; Silva, N.; Silveira, M.; Soares Dealmeida, S.; Torres-Lezama, A.; Vásquez-Martínez, R.; Vieira, I.; Malhi, Y.; Phillips, O. L.

2009-04-01

Xylem density is a physical property of wood that varies between individuals, species and environments. It reflects the physiological strategies of trees that lead to growth, survival and reproduction. Measurements of branch xylem density, ρx, were made for 1653 trees representing 598 species, sampled from 87 sites across the Amazon basin. Measured values ranged from 218 kg m-3 for a Cordia sagotii (Boraginaceae) from Mountagne de Tortue, French Guiana to 1130 kg m-3 for an Aiouea sp. (Lauraceae) from Caxiuana, Central Pará, Brazil. Analysis of variance showed significant differences in average ρx across regions and sampled plots as well as significant differences between families, genera and species. A partitioning of the total variance in the dataset showed that species identity (family, genera and species) accounted for 33% with environment (geographic location and plot) accounting for an additional 26%; the remaining "residual" variance accounted for 41% of the total variance. Variations in plot means, were, however, not only accountable by differences in species composition because xylem density of the most widely distributed species in our dataset varied systematically from plot to plot. Thus, as well as having a genetic component, branch xylem density is a plastic trait that, for any given species, varies according to where the tree is growing in a predictable manner. Within the analysed taxa, exceptions to this general rule seem to be pioneer species belonging for example to the Urticaceae whose branch xylem density is more constrained than most species sampled in this study. These patterns of variation of branch xylem density across Amazonia suggest a large functional diversity amongst Amazonian trees which is not well understood.

Observational Measures of Implementer Fidelity for a School-based Preventive Intervention: Development, Reliability and Validity

PubMed Central

Cross, Wendi; West, Jennifer; Wyman, Peter A.; Schmeelk-Cone, Karen; Xia, Yinglin; Tu, Xin; Teisl, Michael; Brown, C. Hendricks; Forgatch, Marion

2014-01-01

Current measures of implementer fidelity often fail to adequately measure core constructs of adherence and competence, and their relationship to outcomes can be mixed. To address these limitations, we used observational methods to assess these constructs and their relationships to proximal outcomes in a randomized trial of a school-based preventive intervention (Rochester Resilience Project) designed to strengthen emotion self-regulation skills in 1st–3rd graders with elevated aggressive-disruptive behaviors. Within the intervention group (n = 203), a subsample (n = 76) of students was selected to reflect the overall sample. Implementers were 10 paraprofessionals. Videotaped observations of three lessons from Year 1 of the intervention (14 lessons) were coded for each implementer-child dyad on Adherence (content) and Competence (quality). Using multi-level modeling we examined how much of the variance in the fidelity measures was attributed to implementer and to the child within implementer. Both measures had large and significant variance accounted for by implementer (Competence, 68%; Adherence, 41%); child within implementer did not account for significant variance indicating that ratings reflected stable qualities of the implementer rather than the child. Raw Adherence and Competence scores shared 46% of variance (r = .68). Controlling for baseline differences and age, the amount (Adherence) and quality (Competence) of program delivered predicted children’s enhanced response to the intervention on both child and parent reports after six months, but not on teacher report of externalizing behavior. Our findings support the use of multiple observations for measuring fidelity and that adherence and competence are important components of fidelity which could be assessed by many programs using these methods. PMID:24736951

How neglect and punitiveness influence emotion knowledge.

PubMed

Sullivan, Margaret Wolan; Carmody, Dennis P; Lewis, Michael

2010-06-01

To explore whether punitive parenting styles contribute to early-acquired emotion knowledge deficits observable in neglected children, we observed 42 preschool children's emotion knowledge, expression recognition time, and IQ. The children's mothers completed the Parent-Child Conflict Tactics Scales to assess the recent use of three types of discipline strategies (nonviolent, physically punitive, and psychological aggression), as well as neglectful parenting. Fifteen of the children were identified as neglected by Child Protective Services (CPS) reports; 27 children had no record of CPS involvement and served as the comparison group. There were no differences between the neglect and comparison groups in the demographic factors of gender, age, home language, minority status, or public assistance, nor on IQ. Hierarchical multiple regression modeling showed that neglect significantly predicted emotion knowledge. The addition of IQ contributed a significant amount of additional variance to the model and maintained the fit. Adding parental punitiveness in the final stage contributed little additional variance and did not significantly improve the fit. Thus, deficits in children's emotion knowledge may be due primarily to lower IQ or neglect. IQ was unrelated to speed of emotion recognition. Punitiveness did not directly contribute to emotion knowledge deficits but appeared in exploratory analysis to be related to speed of emotion recognition.

Person-organization fit and organizational identification as predictors of positive and negative work-home interactions.

PubMed

Merecz, Dorota; Andysz, Aleksandra

2014-01-01

The aim of the presented research was to explore the links between complementary and supplementary dimensions of Person-Organization fit (P-O fit), organizational identification (OI) and negative (WHI(-)) versus positive (WHI(+)) work-home interactions. It was assumed that both complementary and supplementary P-O fit and OI were positively related to WHI(+) and negatively to WHI(-). The study was conducted on a large sample of Polish blue and white collar workers. The subjects were interviewed by means of questionnaires measuring: supplementary and complementary dimensions of P-O fit, OI and WHI. General work ability and demographic variables were also controlled in the study, and statistical analysis of ANOVA, pairwise comparison as well as regression were performed. P-O fit and OI differentiated the subjects in terms of WHI. For women supplementary fit was a significant predictor of WHI(-) and explained 12% of its variance, for men it was complementary fit with the number of working days per week and the level of education, which explained 22% of variance. Supplementary fit and OI explained 16% of WHI(+) variance in women; OI, tenure at the main place of employment and the level of education explained 8% of WHI(+) variance in men. It has been proven that not only are the effects of P-O fit and OI limited to the work environment but they also permeate boundaries between work and home and influence private life - good level of P-O fit and good OI play facilitating role in the positive spillover between work and home. Gender differences in the significance and predictive values of P-O fit and OI for WHI were also found. The innovative aspect of the work is the inclusion of P-O fit and OI in the range of significant predictors of work-home interaction. The results can serve as rationale for employers that improvement of P-O fit and employees' organizational identification should be included in work-life balance programs.

Individual differences in selective attention predict speech identification at a cocktail party.

PubMed

Oberfeld, Daniel; Klöckner-Nowotny, Felicitas

2016-08-31

Listeners with normal hearing show considerable individual differences in speech understanding when competing speakers are present, as in a crowded restaurant. Here, we show that one source of this variance are individual differences in the ability to focus selective attention on a target stimulus in the presence of distractors. In 50 young normal-hearing listeners, the performance in tasks measuring auditory and visual selective attention was associated with sentence identification in the presence of spatially separated competing speakers. Together, the measures of selective attention explained a similar proportion of variance as the binaural sensitivity for the acoustic temporal fine structure. Working memory span, age, and audiometric thresholds showed no significant association with speech understanding. These results suggest that a reduced ability to focus attention on a target is one reason why some listeners with normal hearing sensitivity have difficulty communicating in situations with background noise.

Digit Span as a measure of everyday attention: a study of ecological validity.

PubMed

Groth-Marnat, Gary; Baker, Sonya

2003-12-01

This study investigated the effectiveness of the WAIS-III Digit Span subtest to predict the everyday attention of 75 participants with heterogeneous neurological conditions who were administered the Digit Span subtest as well as the ecologically valid Test of Everyday Attention. In addition, the more visually oriented Picture Completion subtest along with the verbally loaded National Adult Reading Test were administered. Analysis indicated that, although Digit Span was a weak but statistically significant predictor of attentional ability (accounting for 12.7% of the unique variance). Picture Completion was a somewhat stronger predictor (accounting for 19% of the unique variance). The weak association of Digit Span and the Test of Everyday Attention, along with the finding that Picture Completion was a better predictor of performance on the Test of Everyday Attention, question the clinical utility of using Digit Span as a measure of everyday attention.

Correlations for Adolescent Resilience Scale with big five personality traits.

PubMed

Nakaya, Motoyuki; Oshio, Atsushi; Kaneko, Hitoshi

2006-06-01

Currently, individuals tend to encounter many unavoidable, painful events and hardships in the process of growth and development. To lead one's life adapting to these social conditions, it is necessary to maintain one's mental health even while experiencing challenging events; in other words, resilience is required. This study of 130 undergraduates focused on the Adolescent Resilience Scale which assesses capacity for successful adaptation despite challenging or threatening circumstances and examined correlations with scores on the Big Five Personality Inventory. A significant negative correlation of -.59 (p<.001) was noted for scores on the Adolescent Resilience Scale and the Neuroticism dimension of the Big Five Personality Inventory, accounting for 35% of the variance, and positive values with the Extraversion, Openness, and Conscientiousness dimensions (rs= .37, .40, .48, accounting for 14, 16, and 18% of the variance, respectively. Personalities of adolescents who have psychological traits leading to resilience may be partially predicted using these results.

Statistical modelling of growth using a mixed model with orthogonal polynomials.

PubMed

Suchocki, T; Szyda, J

2011-02-01

In statistical modelling, the effects of single-nucleotide polymorphisms (SNPs) are often regarded as time-independent. However, for traits recorded repeatedly, it is very interesting to investigate the behaviour of gene effects over time. In the analysis, simulated data from the 13th QTL-MAS Workshop (Wageningen, The Netherlands, April 2009) was used and the major goal was the modelling of genetic effects as time-dependent. For this purpose, a mixed model which describes each effect using the third-order Legendre orthogonal polynomials, in order to account for the correlation between consecutive measurements, is fitted. In this model, SNPs are modelled as fixed, while the environment is modelled as random effects. The maximum likelihood estimates of model parameters are obtained by the expectation-maximisation (EM) algorithm and the significance of the additive SNP effects is based on the likelihood ratio test, with p-values corrected for multiple testing. For each significant SNP, the percentage of the total variance contributed by this SNP is calculated. Moreover, by using a model which simultaneously incorporates effects of all of the SNPs, the prediction of future yields is conducted. As a result, 179 from the total of 453 SNPs covering 16 out of 18 true quantitative trait loci (QTL) were selected. The correlation between predicted and true breeding values was 0.73 for the data set with all SNPs and 0.84 for the data set with selected SNPs. In conclusion, we showed that a longitudinal approach allows for estimating changes of the variance contributed by each SNP over time and demonstrated that, for prediction, the pre-selection of SNPs plays an important role.

Mediators of the relation between war experiences and suicidal ideation among former child soldiers in Northern Uganda: the WAYS study.

PubMed

Amone-P'Olak, Kennedy; Lekhutlile, Tlholego Molemane; Meiser-Stedman, Richard; Ovuga, Emilio

2014-09-24

Globally, suicide is a public health burden especially in the aftermath of war. Understanding the processes that define the path from previous war experiences (WE) to current suicidal ideation (SI) is crucial for defining opportunities for interventions. We assessed the extent to which different types of previous WE predict current SI and whether post-war hardships and depression mediate the relations between WE and SI among former child soldiers (FCS) in Northern Uganda. We performed cross-sectional analyses with a sample of 539 FCS (61% male) participating in an on-going longitudinal study. The influence of various types of previous WE on current SI and mediation by post-war hardships and depression were assessed by regression analyses. The following types of war experiences: "witnessing violence", "direct personal harm", "deaths", "Involvement in hostilities", "sexual abuse" and "general war experiences" significantly predicted current SI in a univariable analyses whereas "direct personal harm", "involvement in hostilities", and "sexual abuse" independently predicted current SI in a multivariable analyses. General WE were linked to SI (β = 0.18 (95% CI 0.10 to 0.25)) through post-war hardships (accounting for 69% of the variance in their relationship) and through depression/anxiety (β = 0.17 (95% CI 0.12 to 0.22)) accounting for 65% of the variance in their relationship. The direct relationship between previous WE and current SI reduced but remained marginally significant (β = .08, CI: (.01, .17) for depression/anxiety but not for post-war hardships (β = .09, CI: (-.03, .20). Types of WE should be examined when assessing risks for SI. Interventions to reduce SI should aim to alleviate post-war hardships and treat depression/anxiety.

Postnatal penile growth concurrent with mini-puberty predicts later sex-typed play behavior: Evidence for neurobehavioral effects of the postnatal androgen surge in typically developing boys.

PubMed

Pasterski, Vickie; Acerini, Carlo L; Dunger, David B; Ong, Ken K; Hughes, Ieuan A; Thankamony, Ajay; Hines, Melissa

2015-03-01

The masculinizing effects of prenatal androgens on human neurobehavioral development are well established. Also, the early postnatal surge of androgens in male infants, or mini-puberty, has been well documented and is known to influence physiological development, including penile growth. However, neurobehavioral effects of androgen exposure during mini-puberty are largely unknown. The main aim of the current study was to evaluate possible neurobehavioral consequences of mini-puberty by relating penile growth in the early postnatal period to subsequent behavior. Using multiple linear regression, we demonstrated that penile growth between birth and three months postnatal, concurrent with mini-puberty, significantly predicted increased masculine/decreased feminine behavior assessed using the Pre-school Activities Inventory (PSAI) in 81 healthy boys at 3 to 4years of age. When we controlled for other potential influences on masculine/feminine behavior and/or penile growth, including variance in androgen exposure prenatally and body growth postnally, the predictive value of penile growth in the early postnatal period persisted. More specifically, prenatal androgen exposure, reflected in the measurement of anogenital distance (AGD), and early postnatal androgen exposure, reflected in penile growth from birth to 3months, were significant predictors of increased masculine/decreased feminine behavior, with each accounting for unique variance. Our findings suggest that independent associations of PSAI with AGD at birth and with penile growth during mini-puberty reflect prenatal and early postnatal androgen exposures respectively. Thus, we provide a novel and readily available approach for assessing effects of early androgen exposures, as well as novel evidence that early postnatal aes human neurobehavioral development. Copyright © 2015. Published by Elsevier Inc.

Experimental investigation and modelling of surface roughness and resultant cutting force in hard turning of AISI H13 Steel

NASA Astrophysics Data System (ADS)

Boy, M.; Yaşar, N.; Çiftçi, İ.

2016-11-01

In recent years, turning of hardened steels has replaced grinding for finishing operations. This process is compared to grinding operations; hard turning has higher material removal rates, the possibility of greater process flexibility, lower equipment costs, and shorter setup time. CBN or ceramic cutting tools are widely used hard part machining. For successful application of hard turning, selection of suitable cutting parameters for a given cutting tool is an important step. For this purpose, an experimental investigation was conducted to determine the effects of cutting tool edge geometry, feed rate and cutting speed on surface roughness and resultant cutting force in hard turning of AISI H13 steel with ceramic cutting tools. Machining experiments were conducted in a CNC lathe based on Taguchi experimental design (L16) in different levels of cutting parameters. In the experiments, a Kistler 9257 B, three cutting force components (Fc, Ff and Fr) piezoelectric dynamometer was used to measure cutting forces. Surface roughness measurements were performed by using a Mahrsurf PS1 device. For statistical analysis, analysis of variance has been performed and mathematical model have been developed for surface roughness and resultant cutting forces. The analysis of variance results showed that the cutting edge geometry, cutting speed and feed rate were the most significant factors on resultant cutting force while the cutting edge geometry and feed rate were the most significant factor for the surface roughness. The regression analysis was applied to predict the outcomes of the experiment. The predicted values and measured values were very close to each other. Afterwards a confirmation tests were performed to make a comparison between the predicted results and the measured results. According to the confirmation test results, measured values are within the 95% confidence interval.

Eigentumors for prediction of treatment failure in patients with early-stage breast cancer using dynamic contrast-enhanced MRI: a feasibility study

NASA Astrophysics Data System (ADS)

Chan, H. M.; van der Velden, B. H. M.; E Loo, C.; Gilhuijs, K. G. A.

2017-08-01

We present a radiomics model to discriminate between patients at low risk and those at high risk of treatment failure at long-term follow-up based on eigentumors: principal components computed from volumes encompassing tumors in washin and washout images of pre-treatment dynamic contrast-enhanced (DCE-) MR images. Eigentumors were computed from the images of 563 patients from the MARGINS study. Subsequently, a least absolute shrinkage selection operator (LASSO) selected candidates from the components that contained 90% of the variance of the data. The model for prediction of survival after treatment (median follow-up time 86 months) was based on logistic regression. Receiver operating characteristic (ROC) analysis was applied and area-under-the-curve (AUC) values were computed as measures of training and cross-validated performances. The discriminating potential of the model was confirmed using Kaplan-Meier survival curves and log-rank tests. From the 322 principal components that explained 90% of the variance of the data, the LASSO selected 28 components. The ROC curves of the model yielded AUC values of 0.88, 0.77 and 0.73, for the training, leave-one-out cross-validated and bootstrapped performances, respectively. The bootstrapped Kaplan-Meier survival curves confirmed significant separation for all tumors (P  <  0.0001). Survival analysis on immunohistochemical subgroups shows significant separation for the estrogen-receptor subtype tumors (P  <  0.0001) and the triple-negative subtype tumors (P  =  0.0039), but not for tumors of the HER2 subtype (P  =  0.41). The results of this retrospective study show the potential of early-stage pre-treatment eigentumors for use in prediction of treatment failure of breast cancer.

Accounting for nonsampling error in estimates of HIV epidemic trends from antenatal clinic sentinel surveillance

PubMed Central

Eaton, Jeffrey W.; Bao, Le

2017-01-01

Objectives The aim of the study was to propose and demonstrate an approach to allow additional nonsampling uncertainty about HIV prevalence measured at antenatal clinic sentinel surveillance (ANC-SS) in model-based inferences about trends in HIV incidence and prevalence. Design Mathematical model fitted to surveillance data with Bayesian inference. Methods We introduce a variance inflation parameter σinfl2 that accounts for the uncertainty of nonsampling errors in ANC-SS prevalence. It is additive to the sampling error variance. Three approaches are tested for estimating σinfl2 using ANC-SS and household survey data from 40 subnational regions in nine countries in sub-Saharan, as defined in UNAIDS 2016 estimates. Methods were compared using in-sample fit and out-of-sample prediction of ANC-SS data, fit to household survey prevalence data, and the computational implications. Results Introducing the additional variance parameter σinfl2 increased the error variance around ANC-SS prevalence observations by a median of 2.7 times (interquartile range 1.9–3.8). Using only sampling error in ANC-SS prevalence ( σinfl2=0), coverage of 95% prediction intervals was 69% in out-of-sample prediction tests. This increased to 90% after introducing the additional variance parameter σinfl2. The revised probabilistic model improved model fit to household survey prevalence and increased epidemic uncertainty intervals most during the early epidemic period before 2005. Estimating σinfl2 did not increase the computational cost of model fitting. Conclusions: We recommend estimating nonsampling error in ANC-SS as an additional parameter in Bayesian inference using the Estimation and Projection Package model. This approach may prove useful for incorporating other data sources such as routine prevalence from Prevention of mother-to-child transmission testing into future epidemic estimates. PMID:28296801

Applying the social cognitive perspective to volunteer intention in China: the mediating roles of self-efficacy and motivation.

PubMed

Wang, Ji-Wei; Wei, Chang-Nian; Harada, Koichi; Minamoto, Keiko; Ueda, Kimiyo; Cui, Hong-Wei; Zhang, Cheng-Gang; Cui, Zhi-Ting; Ueda, Atsushi

2011-06-01

When predicting volunteer intention, much attention is paid to the volunteer organization environment (VOE). Given that self-efficacy and motivation have emerged as important predictors of volunteer intention, we adopted a combination of ideas of Bandura's social cognitive theory and Ajzen's theory of planned behavior integrating VOE, self-efficacy and motivation to examine their effects on volunteer intention and to determine whether self-efficacy and motivation mediate the relationship between VOE and volunteer intention. The subjects of this study consisted of 198 community health volunteers in Shanghai city, China. Exploratory factor analysis was performed to identify the factor structure using standard principal component analysis. Six new factors were revealed, including two VOE factors, relation with organization and support from government; two motivation factors, personal attitude and social recognition; self-efficacy and volunteer intention. The results of a hierarchical regression analysis indicated that relation with organization accounted for 14.8% of the variance in volunteer intention, and support from government failed to add significantly to variance in volunteer intention; self-efficacy and personal attitude motivation partially mediated the effects of relation with organization on volunteer intention; social recognition motivation did not mediate the relationship between relation with organization and volunteer intention; and relation with organization, self-efficacy and personal attitude motivation accounted for 33.7% of the variance in volunteer intention. These results provide support for self-efficacy and personal attitude motivation as mediators and provide preliminary insight into the potential mechanisms for predicting volunteer intention and improving volunteering by integrating VOE, self-efficacy and motivation factors.

Refinements to Atlantic basin seasonal hurricane prediction from 1 December

NASA Astrophysics Data System (ADS)

Klotzbach, Philip J.

2008-09-01

Atlantic basin seasonal hurricane predictions have been issued by the Tropical Meteorology Project at Colorado State University since 1984, with early December forecasts being issued every year since early December 1991. These forecasts have yet to show real-time forecast skill, despite several statistical models that have shown considerable hindcast skill. In an effort to improve both hindcast skill and hopefully real-time forecast skill, a modified forecast scheme has been developed using data from 1950 to 2007. Predictors were selected based upon how much variance was explained over the 1950-1989 subperiod. These predictors were then required to explain similar amounts of variance over a latter subperiod from 1990 to 2007. Similar amounts of skill were demonstrated for each of the three predictors selected over the 1950-1989 period, the 1990-2007 period, and the full 1950-2007 period. In addition, significant correlations between individual predictors and physical features known to affect hurricanes during the following August-October (i.e., tropical Atlantic wind shear and sea level pressure changes, ENSO phase changes) were obtained. This scheme uses a new methodology where hindcasts were obtained using linear regression and then ranked to generate final hindcast values. Fifty-four percent of the variance was explained for seasonal Net Tropical Cyclone (NTC) activity over the 1950-2007 period. These hindcasts show considerable differences in landfalling U.S. tropical cyclones, especially for the Florida Peninsula and East Coast. Seven major hurricanes made Florida Peninsula and East Coast landfall during the top 15 largest NTC hindcasts compared with only two major hurricane landfalls in the bottom 15 smallest NTC hindcasts.

Efficient prediction designs for random fields.

PubMed

Müller, Werner G; Pronzato, Luc; Rendas, Joao; Waldl, Helmut

2015-03-01

For estimation and predictions of random fields, it is increasingly acknowledged that the kriging variance may be a poor representative of true uncertainty. Experimental designs based on more elaborate criteria that are appropriate for empirical kriging (EK) are then often non-space-filling and very costly to determine. In this paper, we investigate the possibility of using a compound criterion inspired by an equivalence theorem type relation to build designs quasi-optimal for the EK variance when space-filling designs become unsuitable. Two algorithms are proposed, one relying on stochastic optimization to explicitly identify the Pareto front, whereas the second uses the surrogate criteria as local heuristic to choose the points at which the (costly) true EK variance is effectively computed. We illustrate the performance of the algorithms presented on both a simple simulated example and a real oceanographic dataset. © 2014 The Authors. Applied Stochastic Models in Business and Industry published by John Wiley & Sons, Ltd.

Understanding young and older male drivers' willingness to drive while intoxicated: the predictive utility of constructs specified by the theory of planned behaviour and the prototype willingness model.

PubMed

Rivis, Amanda; Abraham, Charles; Snook, Sarah

2011-05-01

The present study examined the predictive utility of constructs specified by the theory of planned behaviour (TPB) and prototype willingness model (PWM) for young and older male drivers' willingness to drive while intoxicated. A cross-sectional questionnaire was employed. Two hundred male drivers, recruited via a street survey, voluntarily completed measures of attitude, subjective norm, perceived behavioural control, prototype perceptions, and willingness. Findings showed that the TPB and PWM variables explained 65% of the variance in young male drivers' willingness and 47% of the variance in older male drivers' willingness, with the interaction between prototype favourability and similarity contributing 7% to the variance explained in older males' willingness to drive while intoxicated. The findings possess implications for theory, research, and anti-drink driving campaigns. ©2010 The British Psychological Society.

Parent-child feedback predicts sibling contrast: using twin studies to test theories of parent-offspring interaction in infant behavior.

PubMed

Eaves, Lindon J; Silberg, Judy L

2005-02-01

Several studies report apparent sibling contrast effects in analyses of twin resemblance. In the presence of genetic differences, contrast effects reduce the dizygotic (DZ) twin correlation relative to that in monozygotic (MZ) twins and produce higher DZ than MZ variance. Explanations of contrast effects are typically cast in terms of direct social interaction between twins or an artifact of the process of rating children by their parents. We outline a model for sibling imitation and contrast effects that depends on social interaction between parents and children. In addition to predicting the observed pattern of twin variances and covariances, the parental mediation of child imitation and contrast effects leads to differences in the variance of parents of MZ and DZ twins and differences between the correlations of parents with their MZ and DZ children.

[Theory, method and application of method R on estimation of (co)variance components].

PubMed

Liu, Wen-Zhong

2004-07-01

Theory, method and application of Method R on estimation of (co)variance components were reviewed in order to make the method be reasonably used. Estimation requires R values,which are regressions of predicted random effects that are calculated using complete dataset on predicted random effects that are calculated using random subsets of the same data. By using multivariate iteration algorithm based on a transformation matrix,and combining with the preconditioned conjugate gradient to solve the mixed model equations, the computation efficiency of Method R is much improved. Method R is computationally inexpensive,and the sampling errors and approximate credible intervals of estimates can be obtained. Disadvantages of Method R include a larger sampling variance than other methods for the same data,and biased estimates in small datasets. As an alternative method, Method R can be used in larger datasets. It is necessary to study its theoretical properties and broaden its application range further.

The importance of personality and parental styles on optimism in adolescents.

PubMed

Zanon, Cristian; Bastianello, Micheline Roat; Pacico, Juliana Cerentini; Hutz, Claudio Simon

2014-01-01

Some studies have suggested that personality factors are important to optimism development. Others have emphasized that family relations are relevant variables to optimism. This study aimed to evaluate the importance of parenting styles to optimism controlling for the variance accounted for by personality factors. Participants were 344 Brazilian high school students (44% male) with mean age of 16.2 years (SD = 1) who answered personality, optimism, responsiveness and demandingness scales. Hierarchical regression analyses were conducted having personality factors (in the first step) and maternal and paternal parenting styles, and demandingness and responsiveness (in the second step) as predictive variables and optimism as the criterion. Personality factors, especially neuroticism (β = -.34, p < .01), extraversion (β = .26, p < .01) and agreeableness (β = .16, p < .01), accounted for 34% of the optimism variance and insignificant variance was predicted exclusively by parental styles (1%). These findings suggest that personality is more important to optimism development than parental styles.

The role of executive functioning in memory performance in pediatric focal epilepsy

PubMed Central

Sepeta, Leigh N.; Casaletto, Kaitlin Blackstone; Terwilliger, Virginia; Facella-Ervolini, Joy; Sady, Maegan; Mayo, Jessica; Gaillard, William D.; Berl, Madison M.

2016-01-01

Objective Learning and memory are essential for academic success and everyday functioning, but the pattern of memory skills and its relationship to executive functioning in children with focal epilepsy is not fully delineated. We address a gap in the literature by examining the relationship between memory and executive functioning in a pediatric focal epilepsy population. Methods Seventy children with focal epilepsy and 70 typically developing children matched on age, intellectual functioning, and gender underwent neuropsychological assessment, including measures of intelligence (WASI/DAS), as well as visual (CMS Dot Locations) and verbal episodic memory (WRAML Story Memory and CVLT-C). Executive functioning was measured directly (WISC-IV Digit Span Backward; CELF-IV Recalling Sentences) and by parent report (Behavior Rating Inventory of Executive Function (BRIEF)). Results Children with focal epilepsy had lower delayed free recall scores than controls across visual and verbal memory tasks (p = 0.02; partial η2 = .12). In contrast, recognition memory performance was similar for patients and controls (p = 0.36; partial η2 = .03). Children with focal epilepsy demonstrated difficulties in working memory (p = 0.02; partial η2 = .08) and planning/organization (p = 0.02) compared to controls. Working memory predicted 9–19% of the variance in delayed free recall for verbal and visual memory; organization predicted 9–10% of the variance in verbal memory. Patients with both left and right focal epilepsy demonstrated more difficulty on verbal versus visual tasks (p = 0.002). Memory performance did not differ by location of seizure foci (temporal vs. extra-temporal, frontal vs. extra-frontal). Significance Children with focal epilepsy demonstrated memory ability within age-level expectations, but delayed free recall was inefficient compared to typically developing controls. Memory difficulties were not related to general cognitive impairment or seizure localization. Executive functioning accounted for significant variance in memory performance, suggesting that poor executive control negatively influences memory retrieval. PMID:28111742

Reward skewness coding in the insula independent of probability and loss

PubMed Central

Tobler, Philippe N.

2011-01-01

Rewards in the natural environment are rarely predicted with complete certainty. Uncertainty relating to future rewards has typically been defined as the variance of the potential outcomes. However, the asymmetry of predicted reward distributions, known as skewness, constitutes a distinct but neuroscientifically underexplored risk term that may also have an impact on preference. By changing only reward magnitudes, we study skewness processing in equiprobable ternary lotteries involving only gains and constant probabilities, thus excluding probability distortion or loss aversion as mechanisms for skewness preference formation. We show that individual preferences are sensitive to not only the mean and variance but also to the skewness of predicted reward distributions. Using neuroimaging, we show that the insula, a structure previously implicated in the processing of reward-related uncertainty, responds to the skewness of predicted reward distributions. Some insula responses increased in a monotonic fashion with skewness (irrespective of individual skewness preferences), whereas others were similarly elevated to both negative and positive as opposed to no reward skew. These data support the notion that the asymmetry of reward distributions is processed in the brain and, taken together with replicated findings of mean coding in the striatum and variance coding in the cingulate, suggest that the brain codes distinct aspects of reward distributions in a distributed fashion. PMID:21849610

Analysis of job satisfaction, burnout, and intent of respiratory care practitioners to leave the field or the job.

PubMed

Shelledy, D C; Mikles, S P; May, D F; Youtsey, J W

1992-01-01

Increased stress, burnout, and lack of job satisfaction may contribute to a decline in work performance, absenteeism, and intent to leave one's job or field. We undertook to determine organizational, job-specific, and personal predictors of level of burnout among respiratory care practitioners (RCPs). We also examined the relationships among burnout, job satisfaction (JS), absenteeism, and RCPs' intent to leave their job or the field. A pilot-tested assessment instrument was mailed to all active NBRC-credentialed RCPs in Georgia (n = 788). There were 458 usable returns (58% response rate). A random sample of 10% of the nonrespondents (n = 33) was then surveyed by telephone, and the results were compared to those of the mail respondents. Variables were compared to burnout and JS scores by correlational analysis, which was followed by stepwise multiple regression analyses to determine the ability of the independent variables to predict burnout and JS scores when used in combination. There were no significant differences between respondents and sampled nonrespondents in burnout scores (p = 0.56) or JS (p = 0.24). Prediction of burnout: The coefficient of multiple correlation, R2, indicated that in combination the independent variables accounted for 61% of the variance in burnout scores. The strongest predictor of burnout was job stress. Other job-related predictors of burnout were size of department, satisfaction with work, satisfaction with co-workers and co-worker support, job independence and job control, recognition by nursing, and role clarity. Personal-variable predictors were age, number of previous jobs held, social support, and intent to leave the field of respiratory care. Prediction of job satisfaction: R2 indicated that, in combination, the independent variables accounted for 63% of the variance observed in satisfaction with work, 36% of the variance observed in satisfaction with pay, 36% of the variance in satisfaction with promotions, 62% of the variance in satisfaction with supervision, and 48% of the variance in satisfaction with co-workers. Predictors of work-satisfaction level were recognition by physicians and nursing, age, burn-out level, absenteeism, and intent to leave the field. Predictors of level of satisfaction with pay were actual salary, job independence, organizational climate, ease of obtaining time off, job stress, absenteeism, intent to leave the field, and number of dependent children. Predictors of level of satisfaction with promotions were recognition by nursing, participation in decision making, job stress, intent to leave the field, past turnover rates, and absenteeism. Predictors of level of satisfaction with supervision included supervisor support, role clarity, independence, and ease of obtaining time off. The strongest predictor of level of satisfaction with co-workers was co-worker support. As overall level of JS increased, level of burnout decreased significantly (r = -0.59, p less than 0.001). As burnout level increased, increases occurred in absenteeism (r = 0.22, p less than 0.001), intent to leave the job (r = 0.48, p less than 0.001), and intent to leave the field (r = 0.51, p less than 0.001). Reduced job stress, increased job independence and job control, improved role clarity, and higher levels of JS were all associated with lower levels of burnout. Managerial attention to these factors may improve patient care and reduce absenteeism and turnover among RCPs.

Using Theory of Planned Behavior to Predict the Physical Activity of Children: Probing Gender Differences.

PubMed

Wang, Lijuan; Wang, Lin

2015-01-01

The primary objective of this study was to use the theory of planned behavior (TPB) to examine the association between TPB variables and the moderate-to-vigorous physical activity (MVPA) of children in Shanghai, China. Gender differences were also explored. The participants were 353 children (180 boys and 173 girls) aged 9 to 13 years from three primary schools in Shanghai. Accelerometers were used to measure the MVPA duration of the children. Questionnaires that focused on attitude, subjective norms, and perceived behavioral control (PBC) related to MVPA engagement were completed by the participants. Regression analyses revealed that intention, and not PBC, accounted for 9% of the variance in MVPA. Meanwhile, attitude and PBC explained 33% of the variance in intentions to engage in MVPA. In terms of gender differences, TPB performed better in the physical activity (PA) domain for boys than for girls. Furthermore, attitude and PBC were significantly associated with intention among boys, whereas only PBC was significantly related to intention among girls. Practitioners should consider tailoring intervention to address gender differences to increase leisure-time PA participation of children.

A mediational model of racial discrimination and alcohol-related problems among african american college students.

PubMed

Boynton, Marcella H; O'Hara, Ross E; Covault, Jonathan; Scott, Denise; Tennen, Howard

2014-03-01

Racial discrimination has been identified as an important predictor of alcohol-related outcomes for African Americans. The goal of the current study was to extend previously found links between lifetime discrimination, alcohol use, and alcohol problems as well as to elucidate the affective mechanisms underlying these associations, as moderated by gender. A multiple-groups structural equation model was computed using survey data collected from 619 students from a historically Black college/university. The final model provided excellent fit to the data, explaining 6% of the variance in alcohol consumption and 37% of the variance in alcohol problems. Discrimination was a significant predictor of alcohol-related problems but not, by and large, level of use. For men, anger-but not discrimination-specific anger-was a significant partial mediator of the link between discrimination and both alcohol use and alcohol problems. Depression partially mediated the link between discrimination and alcohol problems for both men and women. The results suggest that, for African Americans whose drinking leads to drinking-related problems, discrimination and poor affective self-regulation are highly relevant and predictive factors, especially for men.

Riddle appreciation and reading comprehension in Cantonese-speaking children.

PubMed

Tang, Ivy N Y; To, Carol K S; Weekes, Brendan S

2013-10-01

Inference-making skills are necessary for reading comprehension. Training in riddle appreciation is an effective way to improve reading comprehension among English-speaking children. However, it is not clear whether these methods generalize to other writing systems. The goal of the present study was to investigate the relationship between inference-making skills, as measured by riddle appreciation ability, and reading comprehension performance in typically developing Cantonese-speaking children in the 4th grade. Forty Cantonese-speaking children between the ages of 9;1 (years;months) and 11;0 were given tests of riddle appreciation ability and reading comprehension. Chinese character reading and auditory comprehension abilities were also assessed using tests that had been standardized in Hong Kong. Regression analyses revealed that riddle appreciation ability explained a significant amount of variance in reading comprehension after variance due to character reading skills and auditory comprehension skills were first considered. Orthographic, lexical, morphological, and syntactic riddles were also significantly correlated with reading comprehension. Riddle appreciation ability predicts reading comprehension in Cantonese-speaking 4th-grade children. Therefore, training Cantonese speakers in riddle appreciation should improve their reading comprehension.

Gender Performance Differences in Biochemistry

ERIC Educational Resources Information Center

Rauschenberger, Matthew M.; Sweeder, Ryan D.

2010-01-01

This study examined the historical performance of students at Michigan State University in a two-part biochemistry series Biochem I (n = 5,900) and Biochem II (n = 5,214) for students enrolled from 1997 to 2009. Multiple linear regressions predicted 54.9-87.5% of the variance in student from Biochem I grade and 53.8-76.1% of the variance in…

Mass fluctuation kinetics: Capturing stochastic effects in systems of chemical reactions through coupled mean-variance computations

NASA Astrophysics Data System (ADS)

Gómez-Uribe, Carlos A.; Verghese, George C.

2007-01-01

The intrinsic stochastic effects in chemical reactions, and particularly in biochemical networks, may result in behaviors significantly different from those predicted by deterministic mass action kinetics (MAK). Analyzing stochastic effects, however, is often computationally taxing and complex. The authors describe here the derivation and application of what they term the mass fluctuation kinetics (MFK), a set of deterministic equations to track the means, variances, and covariances of the concentrations of the chemical species in the system. These equations are obtained by approximating the dynamics of the first and second moments of the chemical master equation. Apart from needing knowledge of the system volume, the MFK description requires only the same information used to specify the MAK model, and is not significantly harder to write down or apply. When the effects of fluctuations are negligible, the MFK description typically reduces to MAK. The MFK equations are capable of describing the average behavior of the network substantially better than MAK, because they incorporate the effects of fluctuations on the evolution of the means. They also account for the effects of the means on the evolution of the variances and covariances, to produce quite accurate uncertainty bands around the average behavior. The MFK computations, although approximate, are significantly faster than Monte Carlo methods for computing first and second moments in systems of chemical reactions. They may therefore be used, perhaps along with a few Monte Carlo simulations of sample state trajectories, to efficiently provide a detailed picture of the behavior of a chemical system.

Predicting functional ability in mild cognitive impairment with the Dementia Rating Scale-2.

PubMed

Greenaway, Melanie C; Duncan, Noah L; Hanna, Sherrie; Smith, Glenn E

2012-06-01

We examined the utility of cognitive evaluation to predict instrumental activities of daily living (IADLs) and decisional ability in Mild Cognitive Impairment (MCI). Sixty-seven individuals with single-domain amnestic MCI were administered the Dementia Rating Scale-2 (DRS-2) as well as the Everyday Cognition assessment form to assess functional ability. The DRS-2 Total Scores and Initiation/Perseveration and Memory subscales were found to be predictive of IADLs, with Total Scores accounting for 19% of the variance in IADL performance on average. In addition, the DRS-2 Initiation/Perseveration and Total Scores were predictive of ability to understand information, and the DRS-2 Conceptualization helped predict ability to communicate with others, both key variables in decision-making ability. These findings suggest that performance on the DRS-2, and specific subscales related to executive function and memory, is significantly related to IADLs in individuals with MCI. These cognitive measures are also associated with decision-making-related abilities in MCI.

Identifying the psychological determinants of risky riding: an application of an extended Theory of Planned Behaviour.

PubMed

Chorlton, Kathryn; Conner, Mark; Jamson, Samantha

2012-11-01

The Theory of Planned Behaviour (TPB) plus moral norms, anticipated regret, past behaviour, self-identity and perceived susceptibility was applied to predicting motorcyclists' intention to ride above the speed limit and ride at inappropriate speeds. Past behaviour, control beliefs, attitudes, moral norm, normative beliefs, age and self-identity explained 60% of the variance in motorcyclists' intention to exceed the speed limit on motorways (N=1381). A total of 62% of the variance in motorcyclists' intention to really go for it on rural roads was accounted for, with past behaviour, attitudes, control beliefs, age, normative beliefs, anticipated regret, self-identity, behavioural beliefs and training status being significant (N=1116). Finally, attitudes, past behaviour, control beliefs, moral norm, anticipated regret, behavioural beliefs, normative beliefs, engine size and self-identity explained 57% of the variance in motorcyclists' intention to ride faster than felt safe in order to keep up with the group (N=1940). The belief-based measures also successfully differentiated between those who intended to speed and those who did not. Theoretical and practical implications of the findings are discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Does the Value of Dynamic Assessment in Predicting End-of-First-Grade Mathematics Performance Differ as a Function of English Language Proficiency?

PubMed Central

Seethaler, Pamela M.; Fuchs, Lynn S.; Fuchs, Douglas; Compton, Donald L.

2015-01-01

The purpose of this study was to assess the added value of dynamic assessment (DA) beyond more conventional static measures for predicting individual differences in year-end 1st-grade calculation (CA) and word-problem (WP) performance, as a function of limited English proficiency (LEP) status. At the start of 1st grade, students (129 LEP; 163 non-LEP) were assessed on a brief static mathematics test, an extended static mathematics test, static tests of domain-general abilities associated with CAs and WPs (vocabulary; reasoning), and DA. Near end of 1st grade, they were assessed on CA and WP. Regression analyses indicated that the value of the predictor depends on the predicted outcome and LEP status. In predicting CAs, the extended mathematics test and DA uniquely explained variance for LEP children, with stronger predictive value for the extended mathematics test; for non-LEP children, the extended mathematics test was the only significant predictor. However, in predicting WPs, only DA and vocabulary were uniquely predictive for LEP children, with stronger value for DA; for non-LEP children, the extended mathematics test and DA were comparably uniquely predictive. Neither the brief static mathematics test nor reasoning was significant in predicting either outcome. The potential value of a gated screening process, using an extended mathematics assessment to predict CAs and using DA to predict WPs, is discussed. PMID:26523068

Strategies Used in Coping With a Cancer Diagnosis Predict Meaning in Life for Survivors

PubMed Central

Jim, Heather S.; Richardson, Susan A.; Golden-Kreutz, Deanna M.; Andersen, Barbara L.

2007-01-01

The search for meaning in life is part of the human experience. A negative life event may threaten perceptions about meaning in life, such as the benevolence of the world and one’s sense of harmony and peace. The authors examined the longitudinal relationship between women’s coping with a diagnosis of breast cancer and their self-reported meaning in life 2 years later. Multiple regression analyses revealed that positive strategies for coping predicted significant variance in the sense of meaning in life—feelings of inner peace, satisfaction with one’s current life and the future, and spirituality and faith—and the absence of such strategies predicted reports of loss of meaning and confusion (ps < .01). The importance and process of finding meaning in the context of a life stressor are discussed. PMID:17100503

Cognitive tests predict real-world errors: the relationship between drug name confusion rates in laboratory-based memory and perception tests and corresponding error rates in large pharmacy chains

PubMed Central

Schroeder, Scott R; Salomon, Meghan M; Galanter, William L; Schiff, Gordon D; Vaida, Allen J; Gaunt, Michael J; Bryson, Michelle L; Rash, Christine; Falck, Suzanne; Lambert, Bruce L

2017-01-01

Background Drug name confusion is a common type of medication error and a persistent threat to patient safety. In the USA, roughly one per thousand prescriptions results in the wrong drug being filled, and most of these errors involve drug names that look or sound alike. Prior to approval, drug names undergo a variety of tests to assess their potential for confusability, but none of these preapproval tests has been shown to predict real-world error rates. Objectives We conducted a study to assess the association between error rates in laboratory-based tests of drug name memory and perception and real-world drug name confusion error rates. Methods Eighty participants, comprising doctors, nurses, pharmacists, technicians and lay people, completed a battery of laboratory tests assessing visual perception, auditory perception and short-term memory of look-alike and sound-alike drug name pairs (eg, hydroxyzine/hydralazine). Results Laboratory test error rates (and other metrics) significantly predicted real-world error rates obtained from a large, outpatient pharmacy chain, with the best-fitting model accounting for 37% of the variance in real-world error rates. Cross-validation analyses confirmed these results, showing that the laboratory tests also predicted errors from a second pharmacy chain, with 45% of the variance being explained by the laboratory test data. Conclusions Across two distinct pharmacy chains, there is a strong and significant association between drug name confusion error rates observed in the real world and those observed in laboratory-based tests of memory and perception. Regulators and drug companies seeking a validated preapproval method for identifying confusing drug names ought to consider using these simple tests. By using a standard battery of memory and perception tests, it should be possible to reduce the number of confusing look-alike and sound-alike drug name pairs that reach the market, which will help protect patients from potentially harmful medication errors. PMID:27193033

Do infant vocabulary skills predict school-age language and literacy outcomes?

PubMed

Duff, Fiona J; Reen, Gurpreet; Plunkett, Kim; Nation, Kate

2015-08-01

Strong associations between infant vocabulary and school-age language and literacy skills would have important practical and theoretical implications: Preschool assessment of vocabulary skills could be used to identify children at risk of reading and language difficulties, and vocabulary could be viewed as a cognitive foundation for reading. However, evidence to date suggests predictive ability from infant vocabulary to later language and literacy is low. This study provides an investigation into, and interpretation of, the magnitude of such infant to school-age relationships. Three hundred British infants whose vocabularies were assessed by parent report in the 2nd year of life (between 16 and 24 months) were followed up on average 5 years later (ages ranged from 4 to 9 years), when their vocabulary, phonological and reading skills were measured. Structural equation modelling of age-regressed scores was used to assess the strength of longitudinal relationships. Infant vocabulary (a latent factor of receptive and expressive vocabulary) was a statistically significant predictor of later vocabulary, phonological awareness, reading accuracy and reading comprehension (accounting for between 4% and 18% of variance). Family risk for language or literacy difficulties explained additional variance in reading (approximately 10%) but not language outcomes. Significant longitudinal relationships between preliteracy vocabulary knowledge and subsequent reading support the theory that vocabulary is a cognitive foundation of both reading accuracy and reading comprehension. Importantly however, the stability of vocabulary skills from infancy to later childhood is too low to be sufficiently predictive of language outcomes at an individual level - a finding that fits well with the observation that the majority of 'late talkers' resolve their early language difficulties. For reading outcomes, prediction of future difficulties is likely to be improved when considering family history of language/literacy difficulties alongside infant vocabulary levels. © 2015 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd, on behalf of Association for Child and Adolescent Mental Health.

On the competition among aerosol number, size and composition in predicting CCN variability: a multi-annual field study in an urbanized desert.

PubMed

Crosbie, E; Youn, J-S; Balch, B; Wonaschütz, A; Shingler, T; Wang, Z; Conant, W C; Betterton, E A; Sorooshian, A

2015-02-10

A 2-year data set of measured CCN (cloud condensation nuclei) concentrations at 0.2 % supersaturation is combined with aerosol size distribution and aerosol composition data to probe the effects of aerosol number concentrations, size distribution and composition on CCN patterns. Data were collected over a period of 2 years (2012-2014) in central Tucson, Arizona: a significant urban area surrounded by a sparsely populated desert. Average CCN concentrations are typically lowest in spring (233 cm -3 ), highest in winter (430 cm -3 ) and have a secondary peak during the North American monsoon season (July to September; 372 cm -3 ). There is significant variability outside of seasonal patterns, with extreme concentrations (1 and 99 % levels) ranging from 56 to 1945 cm -3 as measured during the winter, the season with highest variability. Modeled CCN concentrations based on fixed chemical composition achieve better closure in winter, with size and number alone able to predict 82% of the variance in CCN concentration. Changes in aerosol chemical composition are typically aligned with changes in size and aerosol number, such that hygroscopicity can be parameterized even though it is still variable. In summer, models based on fixed chemical composition explain at best only 41% (pre-monsoon) and 36% (monsoon) of the variance. This is attributed to the effects of secondary organic aerosol (SOA) production, the competition between new particle formation and condensational growth, the complex interaction of meteorology, regional and local emissions and multi-phase chemistry during the North American monsoon. Chemical composition is found to be an important factor for improving predictability in spring and on longer timescales in winter. Parameterized models typically exhibit improved predictive skill when there are strong relationships between CCN concentrations and the prevailing meteorology and dominant aerosol physicochemical processes, suggesting that similar findings could be possible in other locations with comparable climates and geography.

The influence of spelling ability on handwriting production: children with and without dyslexia.

PubMed

Sumner, Emma; Connelly, Vincent; Barnett, Anna L

2014-09-01

Current models of writing do not sufficiently address the complex relationship between the 2 transcription skills: spelling and handwriting. For children with dyslexia and beginning writers, it is conceivable that spelling ability will influence rate of handwriting production. Our aim in this study was to examine execution speed and temporal characteristics of handwriting when completing sentence-copying tasks that are free from composing demands and to determine the predictive value of spelling, pausing, and motor skill on handwriting production. Thirty-one children with dyslexia (Mage = 9 years 4 months) were compared with age-matched and spelling-ability matched children (Mage = 6 years 6 months). A digital writing tablet and Eye and Pen software were used to analyze handwriting. Children with dyslexia were able to execute handwriting at the same speed as the age-matched peers. However, they wrote less overall and paused more frequently while writing, especially within words. Combined spelling ability and within-word pausing accounted for over 76% of the variance in handwriting production of children with dyslexia, demonstrating that productivity relies on spelling capabilities. Motor skill did not significantly predict any additional variance in handwriting production. Reading ability predicted performance of the age-matched group, and pausing predicted performance for the spelling-ability group. The findings from the digital writing tablet highlight the interactive relationship between the transcription skills and how, if spelling is not fully automatized, it can constrain the rate of handwriting production. Practical implications are also addressed, emphasizing the need for more consideration to be given to what common handwriting tasks are assessing as a whole.

A Prospective Investigation of Prenatal Mood and Childbirth Perceptions in an Ethnically Diverse, Low-Income Sample

PubMed Central

Congdon, Jayme L.; Adler, Nancy E.; Epel, Elissa S.; Laraia, Barbara A.; Bush, Nicole R.

2017-01-01

Introduction Few studies have examined prenatal mood as a means to identify women at risk for negative childbirth experiences. We explore associations between prenatal mood and birth perceptions in a socioeconomically diverse, American sample. Methods We conducted a prospective study of 136 predominantly low-income and ethnic minority women of mixed parity. Prenatal measures of perceived stress, pregnancy-related anxiety, and depressive symptoms were used to predict maternal perceptions of birth experiences one month postpartum using the Childbirth Experience Questionnaire (CEQ; 1). Results After adjusting for sociodemographic variables and mode of delivery, higher third trimester stress predicted worse CEQ total scores. This association was predominantly explained by two CEQ domains: own capacity (e.g. feelings of control and capability) and perceived safety. Pregnancy-related anxiety and depressive symptoms correlated with perceived stress, though neither independently predicted birth experience. Unplanned cesareans were associated with a worse CEQ total score. Vaginal delivery predicted greater perceived safety. Altogether, sociodemographic covariates, mode of delivery, and prenatal mood accounted for 35% of the variance in birth experience (p<.001). Discussion Our finding that prenatal stress explains a significant and likely clinically meaningful proportion of the variance in birth experience suggests that women perceive and recall their birth experiences through a lens that is partially determined by preexisting personal circumstances and emotional reserves. Since childbirth perceptions have implications for maternal and child health, patient satisfaction, and healthcare expenditures, these findings warrant consideration of prenatal stress screening to target intervention for women at risk for negative birth experiences. PMID:26948850

The relationship between approaches to study and academic performance among Australian undergraduate occupational therapy students.

PubMed

Brown, Ted; Murdolo, Yuki

2017-06-01

The academic success and degree completion of tertiary students depends on their academic performance (AP), commonly measured by the percentage grades for the units they complete. No research has examined whether occupational therapy students' approaches to study are predictive of their AP. This study investigated whether approaches to study were predictive of the AP among a group of Australian undergraduate occupational therapy students. A total of 376 undergraduate occupational therapy students completed the Approaches and Study Skills Inventory for Students (ASSIST). Regression analysis was conducted using a range of demographic characteristics and the ASSIST scores as independent variables with students' self-reported by their self-reported mean percentage grade range (as a proxy indicator of their AP) as the dependent variable. The deep and the strategic approaches to study were not significantly correlated with occupational therapy students' AP. The ASSIST fear of failure subscale of the surface approach to study had a unique contribution to AP, accounting for 1.3% of its total variance. Occupational therapy students' year level of enrolment made a unique contribution to their AP, accounting for 4.2% of the total variance. Age and gender made a unique contribution to AP as well although their impact was small. Undergraduate occupational therapy students' approaches to study were predictive of their AP to a very limited degree. However, their AP was predicted by a number of demographic variables, including age, gender and year level of enrolment. Further study in this area is recommended. © 2016 Occupational Therapy Australia.

A Prospective Investigation of Prenatal Mood and Childbirth Perceptions in an Ethnically Diverse, Low-Income Sample.

PubMed

Congdon, Jayme L; Adler, Nancy E; Epel, Elissa S; Laraia, Barbara A; Bush, Nicole R

2016-06-01

Few studies have examined prenatal mood as a means to identify women at risk for negative childbirth experiences. We explore associations between prenatal mood and birth perceptions in a socioeconomically diverse, American sample. We conducted a prospective study of 136 predominantly low-income and ethnic minority women of mixed parity. Prenatal measures of perceived stress, pregnancy-related anxiety, and depressive symptoms were used to predict maternal perceptions of birth experiences 1 month postpartum, using the childbirth experience questionnaire (CEQ; 1). After adjusting for sociodemographic variables and mode of delivery, higher third-trimester stress predicted worse CEQ total scores. This association was predominantly explained by two CEQ domains: own capacity (e.g., feelings of control and capability), and perceived safety. Pregnancy-related anxiety and depressive symptoms correlated with perceived stress, though neither independently predicted birth experience. An unplanned cesarean delivery was associated with a worse CEQ total score. Vaginal delivery predicted greater perceived safety. Altogether, sociodemographic covariates, mode of delivery, and prenatal mood accounted for 35 percent of the variance in birth experience (p < 0.001). Our finding that prenatal stress explains a significant and likely clinically meaningful proportion of the variance in birth experience suggests that women perceive and recall their birth experiences through a lens that is partially determined by preexisting personal circumstances and emotional reserves. Since childbirth perceptions have implications for maternal and child health, patient satisfaction, and health care expenditures, these findings warrant consideration of prenatal stress screening to target intervention for women at risk for negative birth experiences. © 2016 Wiley Periodicals, Inc.

Ability of admissions criteria to predict early academic performance among students of health science colleges at King Saud University, Saudi Arabia.

PubMed

Alhadlaq, Adel M; Alshammari, Osama F; Alsager, Saleh M; Neel, Khalid A Fouda; Mohamed, Ashry G

2015-06-01

The aim of this study was to evaluate the ability of admissions criteria at King Saud University (KSU), Riyadh, Saudi Arabia, to predict students' early academic performance at three health science colleges (medicine, dentistry, and pharmacy). A retrospective cohort study was conducted with data from the records of students enrolled in the three colleges from the 2008-09 to 2010-11 academic years. The admissions criteria-high school grade average (HSGA), aptitude test (APT) score, and achievement test (ACT) score-were the independent variables. The dependent variable was the average of students' first- and second-year grade point average (GPA). The results showed that the ACT was a better predictor of the students' early academic performance than the HSGA (β=0.368, β=0.254, respectively). No significant relationship was found between the APT and students' early academic performance (β=-0.019, p>0.01). The ACT was most predictive for pharmacy students (β=0.405), followed by dental students (β =0.392) and medical students (β=0.195). Overall, the current admissions criteria explained only 25.5% of the variance in the students' early academic performance. While the ACT and HSGA were found to be predictive of students' early academic performance in health colleges at KSU, the APT was not a strong predictor. Since the combined current admissions criteria for the health science colleges at KSU were weak predictors of the variance in early academic performance, it may be necessary to consider noncognitive evaluation methods during the admission process.

Recent victimization increases risk for violence in justice-involved persons with mental illness.

PubMed

Sadeh, Naomi; Binder, Renée L; McNiel, Dale E

2014-04-01

A large body of research has examined relationships between distal experiences of victimization and the likelihood of engaging in violence later in life. Less is known about the influence of recent violent victimization on risk for violence perpetration. To our knowledge, this is the first study to examine prospectively whether recent victimization in adulthood increases the risk of future violence. Specifically, the present study assessed the incremental validity of recent violent victimization in the prediction of future violence in a sample of justice-involved adults with serious mental illness. The study examined (a) whether recent experiences of violent victimization (i.e., within 6 months of the baseline assessment) predicted a greater likelihood of perpetrating violence in the next year, and (b) whether inclusion of recent victimization enhanced the predictive validity of a model of violence risk in a sample of justice-involved adults with severe mental illness (N = 167). Hierarchical logistic regression analyses indicated that exposure to recent violent victimization at the baseline assessment predicted a greater likelihood of engaging in violent behavior during the year follow-up period. Additionally, recent exposure to violence at the baseline assessment continued to explain a significant amount of variance in a model of future violence perpetration above the variance accounted for by well-established violence risk factors. Taken together, the findings suggest that recent victimization is important to consider in understanding and evaluating risk of violence by persons with mental disorders who are involved in the criminal justice system. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Factors associated with bone turnover and speed of sound in early and late-pubertal females.

PubMed

Klentrou, Panagiota; Ludwa, Izabella A; Falk, Bareket

2011-10-01

This cross-sectional study examines whether maturity, body composition, physical activity, dietary intake, and hormonal concentrations are related to markers of bone turnover and tibial speed of sound (tSOS) in premenarcheal (n = 20, 10.1 ± 1.1 years) and postmenarcheal girls (n = 28, aged 15.0 ± 1.4 years). Somatic maturity was evaluated using years from age of peak height velocity (aPHV). Daily dietary intake was assessed with a 24-h recall interview, and moderate to very vigorous physical activity (MVPA) was measured using accelerometry. Plasma levels of 25-OH vitamin D, serum levels of insulin-like growth-factor 1 (IGF-1) and leptin, and serum levels of bone turnover markers including osteocalcin (OC), bone-specific alkaline phosphatase (BAP) and cross-linked N-teleopeptide of type I collagen (NTX) were measured using ELISA. OC, BAP, and NTX were significantly higher while IGF-1 and tSOS were lower in the premenarcheal group. The premenarcheal girls were more active and had higher daily energy intake relative to their body mass but there were no group differences in body mass index percentile. Maturity predicted 40%-57% of the variance in bone turnover markers. Additionally, daily energy intake was a significant predictor of OC, especially in the postmenarcheal group. IGF-1 and MVPA were significant predictors of BAP in the group as a whole. However, examined separately, IGF-1 was a predictor of BAP in the premenarcheal group while MVPA was a predictor in the postmenarcheal group. Adiposity and leptin were both negative predictors of tSOS, with leptin being specifically predictive in the postmenarcheal group. In conclusion, while maturity was the strongest predictor of bone markers and tSOS, dietary intake, physical activity, body composition, and hormonal factors further contribute to the variance in bone turnover and bone SOS in young Caucasian females. Further, the predicting factors of bone turnover and tSOS were different within each maturity group.

Cortisol Secretion and Change in Sleep Problems in Early Childhood: Moderation by Maternal Overcontrol

PubMed Central

Kiel, Elizabeth J.; Hummel, Alexandra C.; Luebbe, Aaron M.

2015-01-01

Childhood sleep problems are prevalent and relate to a wide range of negative psychological outcomes. However, it remains unclear how biological processes, such as HPA activity, may predict sleep problems over time in childhood in the context of certain parenting environments. Fifty-one mothers and their 18–20 month-old toddlers participated in a short-term longitudinal study assessing how shared variance among morning levels, diurnal change, and nocturnal change in toddlers’ cortisol secretion predicted change in sleep problems in the context of maternal overprotection and critical control. A composite characterized by low variability in, and, to a lesser extent, high morning values of cortisol, predicted increasing sleep problems from age 2 to age 3 when mothers reported high critical control. Results suggest value in assessing shared variance among different indices of cortisol secretion patterns and the interaction between cortisol and the environment in predicting sleep problems in early childhood. PMID:25766262

Normative morphometric data for cerebral cortical areas over the lifetime of the adult human brain.

PubMed

Potvin, Olivier; Dieumegarde, Louis; Duchesne, Simon

2017-08-01

Proper normative data of anatomical measurements of cortical regions, allowing to quantify brain abnormalities, are lacking. We developed norms for regional cortical surface areas, thicknesses, and volumes based on cross-sectional MRI scans from 2713 healthy individuals aged 18 to 94 years using 23 samples provided by 21 independent research groups. The segmentation was conducted using FreeSurfer, a widely used and freely available automated segmentation software. Models predicting regional cortical estimates of each hemisphere were produced using age, sex, estimated total intracranial volume (eTIV), scanner manufacturer, magnetic field strength, and interactions as predictors. The explained variance for the left/right cortex was 76%/76% for surface area, 43%/42% for thickness, and 80%/80% for volume. The mean explained variance for all regions was 41% for surface areas, 27% for thicknesses, and 46% for volumes. Age, sex and eTIV predicted most of the explained variance for surface areas and volumes while age was the main predictors for thicknesses. Scanner characteristics generally predicted a limited amount of variance, but this effect was stronger for thicknesses than surface areas and volumes. For new individuals, estimates of their expected surface area, thickness and volume based on their characteristics and the scanner characteristics can be obtained using the derived formulas, as well as Z score effect sizes denoting the extent of the deviation from the normative sample. Models predicting normative values were validated in independent samples of healthy adults, showing satisfactory validation R 2 . Deviations from the normative sample were measured in individuals with mild Alzheimer's disease and schizophrenia and expected patterns of deviations were observed. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

Genome-Assisted Prediction of Quantitative Traits Using the R Package sommer.

PubMed

Covarrubias-Pazaran, Giovanny

2016-01-01

Most traits of agronomic importance are quantitative in nature, and genetic markers have been used for decades to dissect such traits. Recently, genomic selection has earned attention as next generation sequencing technologies became feasible for major and minor crops. Mixed models have become a key tool for fitting genomic selection models, but most current genomic selection software can only include a single variance component other than the error, making hybrid prediction using additive, dominance and epistatic effects unfeasible for species displaying heterotic effects. Moreover, Likelihood-based software for fitting mixed models with multiple random effects that allows the user to specify the variance-covariance structure of random effects has not been fully exploited. A new open-source R package called sommer is presented to facilitate the use of mixed models for genomic selection and hybrid prediction purposes using more than one variance component and allowing specification of covariance structures. The use of sommer for genomic prediction is demonstrated through several examples using maize and wheat genotypic and phenotypic data. At its core, the program contains three algorithms for estimating variance components: Average information (AI), Expectation-Maximization (EM) and Efficient Mixed Model Association (EMMA). Kernels for calculating the additive, dominance and epistatic relationship matrices are included, along with other useful functions for genomic analysis. Results from sommer were comparable to other software, but the analysis was faster than Bayesian counterparts in the magnitude of hours to days. In addition, ability to deal with missing data, combined with greater flexibility and speed than other REML-based software was achieved by putting together some of the most efficient algorithms to fit models in a gentle environment such as R.

Structural Studies of Amorphous Materials by Fluctuation Electron Microscopy

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

Treacy, Michael M. J.

Fluctuation Electron Microscopy (FEM) is a technique that examines the fluctuations in electron scattering across a uniformly thin amorphous sample. The statistics of the intensity fluctuations, mean and variance, reveal any underlying medium-range order present in the structure. The goals of this project were: (1) To determine the fundamentals of the scattering physics that gives rise to the variance signal in fluctuation electron microscopy (FEM); (2) To use these discoveries to find ways to quantify FEM; (3) To apply the FEM method to interesting and technologically important families of amorphous materials, particularly those with important applications in energy-related processes. Excellent progress was made in items (1) and (2). In stage (3) we did not examine the metamict zircons, as proposed. Instead, we examined films of polycrystalline and amorphous semi-conducting diamond. Significant accomplishments are: (1) A Reverse Monte Carlo procedure was successfully implemented to invert FEM data into a structural model. This is computer-intensive, but it demonstrated that diffraction and FEM data from amorphous silicon are most consistent with a paracrystallite model. This means that there is more diamond-like topology present in amorphous silicon than is predicted by the continuous random network model. (2) There is significant displacement decoherence arising in diffraction from amorphous silicon and carbon. The samples are being bombarded by the electron beam and atoms do not stay still while being irradiated – much more than was formerly understood. The atom motions cause the destructive and constructive interferences in the diffraction pattern to fluctuate with time, and it is the time-averaged speckle that is being measured. The variance is reduced by a factor m, 4 ≤ m ≤ 1000, relative to that predicted by kinematical scattering theory. (3) Speckle intensity obeys a gamma distribution, where the mean intensitymore » $$ \\overline{I}\\ $$ and m are the two parameters governing the shape of the gamma distribution profile. m is determined by the illumination spatial coherence, which is normally very high, and mostly by the displacement decoherence within the sample. (4) Amorphous materials are more affected by the electron beam than are crystalline materials. Different samples exhibit different disruptibility, as measured by the effective values of m that fit the data. (5) Understanding the origin of the displacement decoherence better should lead to efficient methods for computing the observed variance from amorphous materials.« less

Symptoms predicting psychosocial impairment in bulimia nervosa.

PubMed

Jenkins, Paul E; Staniford, Jessica; Luck, Amy

2017-05-12

The current study aimed to determine which particular eating disorder (ED) symptoms and related features, such as BMI and psychological distress, uniquely predict impairment in bulimia nervosa (BN). Two hundred and twenty-two adults with BN completed questionnaires assessing ED symptoms, general psychological distress, and psychosocial impairment. Regression analyses were used to determine predictors which account for variance in impairment. Four variables emerged as significant predictors of psychosocial impairment: concerns with eating; concerns with weight and shape; dietary restraint; and general psychological distress. Findings support previous work highlighting the importance of weight and shape concerns in determining ED-related impairment. Other ED symptoms, notably dietary restraint and concerns with eating, were also significant predictors as was psychological distress. Results suggest that cognitive aspects of EDs, in addition to psychological distress, may be more important determinants of impairment than behavioural symptoms, such as binge eating or purging.

Self-Esteem, Social Support, Collectivism, and the Thin-Ideal in Latina College Undergraduates

PubMed Central

Cordero, Elizabeth D.

2010-01-01

Thin-ideal internalization (TII) reflects agreement that thinness equates with beauty. TII is a risk factor for body dissatisfaction and eating pathology; this phenomenon and its correlates, however, are just beginning to be studied in Latina undergraduates. This study examined the ability of self-esteem, social support, and collectivism to predict TII in Latina undergraduates. It was hypothesized that higher levels of self-esteem, social support, and collectivism would predict lower levels of TII. Cross-sectional data were analyzed using multiple regression; the model was significant, p < .01. Although both self-esteem and social support negatively correlated with thin-ideal internalization, only self-esteem accounted for a significant amount of variance. Results indicate that investigations of self-esteem as a protective factor against TII in Latina undergraduates would be fruitful, as would how self-esteem and social support affect the relationship between TII and other variables. Implications and limitations are discussed. PMID:21147052

Physical activity measurement in older adults: relationships with mental health.

PubMed

Parker, Sarah J; Strath, Scott J; Swartz, Ann M

2008-10-01

This study examined the relationship between physical activity (PA) and mental health among older adults as measured by objective and subjective PA-assessment instruments. Pedometers (PED), accelerometers (ACC), and the Physical Activity Scale for the Elderly (PASE) were administered to measure 1 week of PA among 84 adults age 55-87 (mean = 71) years. General mental health was measured using the Positive and Negative Affect Scale (PANAS) and the Satisfaction With Life Scale (SWL). Linear regressions revealed that PA estimated by PED significantly predicted 18.1%, 8.3%, and 12.3% of variance in SWL and positive and negative affect, respectively, whereas PA estimated by the PASE did not predict any mental health variables. Results from ACC data were mixed. Hotelling-William tests between correlation coefficients revealed that the relationship between PED and SWL was significantly stronger than the relationship between PASE and SWL. Relationships between PA and mental health might depend on the PA measure used.

Predictors of Weapon Carrying in Youth Attending Drop-in Centers

PubMed Central

Blumberg, Elaine J.; Liles, Sandy; Kelley, Norma J.; Hovell, Melbourne F.; Bousman, Chad A.; Shillington, Audrey M.; Ji, Ming; Clapp, John

2012-01-01

Objective To test and compare 2 predictive models of weapon carrying in youth (n=308) recruited from 4 drop-in centers in San Diego and Imperial counties. Methods Both models were based on the Behavioral Ecological Model (BEM). Results The first and second models significantly explained 39% and 53% of the variance in weapon carrying, respectively, and both full models shared the significant predictors of being black(−), being Hispanic (−), peer modeling of weapon carrying/jail time(+), and school suspensions(+). Conclusions Results suggest that the BEM offers a generalizable conceptual model that may inform prevention strategies for youth at greatest risk of weapon carrying. PMID:19320622

New York City social workers after 9/11: their attachment, resiliency, and compassion fatigue.

PubMed

Tosone, Carol; Bettmann, Joanna E; Minami, Takuya; Jasperson, Rachael A

2010-01-01

This study examines the relationship between attachment classification, resiliency, and compassion fatigue in New York social workers following 9/11. We used single occasion, quasi-random sampling, surveying 481 social workers living in Manhattan. Hierarchical regression analyses revealed that secure attachment is predictive of the ability to cope with secondary traumatic stress as well as capacity for resilience, explaining approximately 7% of the variance in both compassion fatigue and resiliency. These findings suggest that secure attachment may serve as a source of resilience for social workers, immunizing them from significant compassion fatigue. Such findings have significant implications for clinicians working with traumatized populations.

Low Motivational Incongruence Predicts Successful EEG Resting-state Neurofeedback Performance in Healthy Adults.

PubMed

Diaz Hernandez, Laura; Rieger, Kathryn; Koenig, Thomas

2018-05-15

Neurofeedback is becoming increasingly sophisticated and widespread, although predictors of successful performance still remain scarce. Here, we explored the possible predictive value of psychological factors and report the results obtained from a neurofeedback training study designed to enhance the self-regulation of spontaneous EEG microstates of a particular type (microstate class D). Specifically, we were interested in life satisfaction (including motivational incongruence), body awareness, personality and trait anxiety. These variables were quantified with questionnaires before neurofeedback. Individual neurofeedback success was established by means of linear mixed models that accounted for the amount of observed target state (microstate class D contribution) as a function of time and training condition: baseline, training and transfer (results shown in Diaz Hernandez et al.). We found a series of significant negative correlations between motivational incongruence and mean percentage increase of microstate D during the condition transfer, across-sessions (36% of common variance) and mean percentage increase of microstate D during the condition training, within-session (42% of common variance). There were no significant correlations related to other questionnaires, besides a trend in a sub-scale of the Life Satisfaction questionnaire. We conclude that motivational incongruence may be a potential predictor for neurofeedback success, at least in the current protocol. The finding may be explained by the interfering effect on neurofeedback performance produced by incompatible simultaneously active psychological processes, which are indirectly measured by the Motivational Incongruence questionnaire. Copyright © 2016. Published by Elsevier Ltd.

Posttraumatic growth in people with traumatic long-term spinal cord injury: predictive role of basic hope and coping.

PubMed

Byra, S

2016-06-01

Participants with spinal cord injury (SCI) sustained at least 15 years before the study completed questionnaires measuring posttraumatic growth (PTG), basic hope and coping strategies. To determine contribution of basic hope and coping strategies to accounting for PTG variability in participants with traumatic long-term SCI. Polish rehabilitation centres, foundations and associations implementing social inclusion and professional activation programmes. Participants were enrolled based on their medical history by trained rehabilitation specialists and psychologists. The set of questionnaires included the following: The Post-traumatic Growth Inventory; The Coping Orientations to Problems Experienced (COPE); and Basic Hope Inventory. A study of 169 individuals with paraplegia in the range of PTG showed the highest degree of positive changes in appreciation of life (AL) and the lowest in self-perception. Regression analysis showed that coping strategies such as religion (REL), focus on the problem, humour, alcohol/drug use ideation and basic hope jointly account for 60% of variance of PTG. The highest contribution to accounting for this variability had REL. Also, it was found that coping strategies and basic hope allow to predict variance of individual growth aspects. Age at trauma exposure positively correlated with changes in AL and spiritual change. No significant relationship between growth and age of participants was confirmed. PTG occurring in people with long-term traumatic SCI is primarily manifested in increased AL. Specific coping strategies and basic hope have a significant role in fostering positive changes.

Model test on the relationship feed energy and protein ratio to the production and quality of milk protein

NASA Astrophysics Data System (ADS)

Hartanto, R.; Jantra, M. A. C.; Santosa, S. A. B.; Purnomoadi, A.

2018-01-01

The purpose of this research was to find an appropriate relationship model between the feed energy and protein ratio with the amount of production and quality of milk proteins. This research was conducted at Getasan Sub-district, Semarang Regency, Central Java Province, Indonesia using 40 samples (Holstein Friesian cattle, lactation period II-III and lactation month 3-4). Data were analyzed using linear and quadratic regressions, to predict the production and quality of milk protein from feed energy and protein ratio that describe the diet. The significance of model was tested using analysis of variance. Coefficient of determination (R2), residual variance (RV) and root mean square prediction error (RMSPE) were reported for the developed equations as an indicator of the goodness of model fit. The results showed no relationship in milk protein (kg), milk casein (%), milk casein (kg) and milk urea N (mg/dl) as function of CP/TDN. The significant relationship was observed in milk production (L or kg) and milk protein (%) as function of CP/TDN, both in linear and quadratic models. In addition, a quadratic change in milk production (L) (P = 0.003), milk production (kg) (P = 0.003) and milk protein concentration (%) (P = 0.026) were observed with increase of CP/TDN. It can be concluded that quadratic equation was the good fitting model for this research, because quadratic equation has larger R2, smaller RV and smaller RMSPE than those of linear equation.

Use of principal-component, correlation, and stepwise multiple-regression analyses to investigate selected physical and hydraulic properties of carbonate-rock aquifers

USGS Publications Warehouse

Brown, C. Erwin

1993-01-01

Correlation analysis in conjunction with principal-component and multiple-regression analyses were applied to laboratory chemical and petrographic data to assess the usefulness of these techniques in evaluating selected physical and hydraulic properties of carbonate-rock aquifers in central Pennsylvania. Correlation and principal-component analyses were used to establish relations and associations among variables, to determine dimensions of property variation of samples, and to filter the variables containing similar information. Principal-component and correlation analyses showed that porosity is related to other measured variables and that permeability is most related to porosity and grain size. Four principal components are found to be significant in explaining the variance of data. Stepwise multiple-regression analysis was used to see how well the measured variables could predict porosity and (or) permeability for this suite of rocks. The variation in permeability and porosity is not totally predicted by the other variables, but the regression is significant at the 5% significance level. ?? 1993.

Traumatic Dissociation as a Predictor of Posttraumatic Stress Disorder in South African Female Rape Survivors

PubMed Central

Nöthling, Jani; Lammers, Kees; Martin, Lindi; Seedat, Soraya

2015-01-01

Abstract Women survivors of rape are at an increased risk for posttraumatic stress disorder (PTSD). Traumatic dissociation has been identified as a precursor of PTSD. This study assessed the predictive potential of traumatic dissociation in PTSD and depression development. The study followed a longitudinal, prospective design. Ninety-seven female rape survivors were recruited from 2 clinics in Cape Town, South Africa. Clinical interviews and symptom status assessments of the participants were completed to measure dissociation, childhood traumas, resilience, depression, and PTSD. Traumatic dissociation was a significant predictor of PTSD and depression. The linear combination of prior dissociation, current dissociation, and resilience significantly explained 20.7% of the variance in PTSD. Dissociation mediated the relationship between resilience and PTSD. As traumatic dissociation significantly predicts PTSD, its early identification and management may reduce the risk of developing PTSD. Interventions focused on promoting resilience may also be successful in reducing the risk of dissociation following rape. PMID:25906104

Self Efficacy in Depression: Bridging the Gap Between Competence and Real World Functioning.

PubMed

Milanovic, Melissa; Ayukawa, Emma; Usyatynsky, Aleksandra; Holshausen, Katherine; Bowie, Christopher R

2018-05-01

We investigated the discrepancy between competence and real-world performance in major depressive disorder (MDD) for adaptive and interpersonal behaviors, determining whether self-efficacy significantly predicts this discrepancy, after considering depressive symptoms. Forty-two participants (Mage = 37.64, 66.67% female) with MDD were recruited from mental health clinics. Competence, self-efficacy, and real-world functioning were evaluated in adaptive and interpersonal domains; depressive symptoms were assessed with the Beck Depression Inventory II. Hierarchical regression analysis identified predictors of functional disability and the discrepancy between competence and real-world functioning. Self-efficacy significantly predicted functioning in the adaptive and interpersonal domains over and above depressive symptoms. Interpersonal self-efficacy accounted for significant variance in the discrepancy between interpersonal competence and functioning beyond symptoms. Using a multilevel, multidimensional approach, we provide the first data regarding relationships among competence, functioning, and self-efficacy in MDD. Self-efficacy plays an important role in deployment of functional skills in everyday life for individuals with MDD.

Single and Multiple Clinical Syndromes in Incarcerated Offenders: Associations With Dissociative Experiences and Emotionality

PubMed Central

Garofalo, Carlo; Velotti, Patrizia; Crocamo, Cristina; Carrà, Giuseppe

2017-01-01

The present study examined the prevalence and correlates of clinical syndromes in a large group (N = 438) of incarcerated violent offenders, looking at differences between inmates with one and those with more than one clinical syndromes. More than a half of the sample (57%) reported clinically relevant symptoms for at least one clinical syndrome (n = 252), and the majority of them (38%) reported more syndromes in comorbidity (n = 169). Increased severity of clinical conditions (none, one, more than one syndrome) corresponded with significantly greater levels of personality disorder traits, psychological symptoms, dissociation, and negative emotionality, with large effect sizes. After controlling for co-occurrence of personality disorder traits and other symptoms, the presence of more than one comorbid syndrome significantly predicted unique variance in dissociation (positively) and positive emotionality (negatively). The presence of one clinical syndrome significantly and positively predicted negative emotionality. Findings support the possibility that the complexity, and not just the presence, of psychopathology could identify different groups of inmates. PMID:27913716

Single and Multiple Clinical Syndromes in Incarcerated Offenders: Associations With Dissociative Experiences and Emotionality.

PubMed

Garofalo, Carlo; Velotti, Patrizia; Crocamo, Cristina; Carrà, Giuseppe

2018-04-01

The present study examined the prevalence and correlates of clinical syndromes in a large group ( N = 438) of incarcerated violent offenders, looking at differences between inmates with one and those with more than one clinical syndromes. More than a half of the sample (57%) reported clinically relevant symptoms for at least one clinical syndrome ( n = 252), and the majority of them (38%) reported more syndromes in comorbidity ( n = 169). Increased severity of clinical conditions (none, one, more than one syndrome) corresponded with significantly greater levels of personality disorder traits, psychological symptoms, dissociation, and negative emotionality, with large effect sizes. After controlling for co-occurrence of personality disorder traits and other symptoms, the presence of more than one comorbid syndrome significantly predicted unique variance in dissociation (positively) and positive emotionality (negatively). The presence of one clinical syndrome significantly and positively predicted negative emotionality. Findings support the possibility that the complexity, and not just the presence, of psychopathology could identify different groups of inmates.

Scalar decay in two-dimensional chaotic advection and Batchelor-regime turbulence

NASA Astrophysics Data System (ADS)

Fereday, D. R.; Haynes, P. H.

2004-12-01

This paper considers the decay in time of an advected passive scalar in a large-scale flow. The relation between the decay predicted by "Lagrangian stretching theories," which consider evolution of the scalar field within a small fluid element and then average over many such elements, and that observed at large times in numerical simulations, associated with emergence of a "strange eigenmode" is discussed. Qualitative arguments are supported by results from numerical simulations of scalar evolution in two-dimensional spatially periodic, time aperiodic flows, which highlight the differences between the actual behavior and that predicted by the Lagrangian stretching theories. In some cases the decay rate of the scalar variance is different from the theoretical prediction and determined globally and in other cases it apparently matches the theoretical prediction. An updated theory for the wavenumber spectrum of the scalar field and a theory for the probability distribution of the scalar concentration are presented. The wavenumber spectrum and the probability density function both depend on the decay rate of the variance, but can otherwise be calculated from the statistics of the Lagrangian stretching history. In cases where the variance decay rate is not determined by the Lagrangian stretching theory, the wavenumber spectrum for scales that are much smaller than the length scale of the flow but much larger than the diffusive scale is argued to vary as k-1+ρ, where k is wavenumber, and ρ is a positive number which depends on the decay rate of the variance γ2 and on the Lagrangian stretching statistics. The probability density function for the scalar concentration is argued to have algebraic tails, with exponent roughly -3 and with a cutoff that is determined by diffusivity κ and scales roughly as κ-1/2 and these predictions are shown to be in good agreement with numerical simulations.

Estimating Additive and Non-Additive Genetic Variances and Predicting Genetic Merits Using Genome-Wide Dense Single Nucleotide Polymorphism Markers

PubMed Central

Su, Guosheng; Christensen, Ole F.; Ostersen, Tage; Henryon, Mark; Lund, Mogens S.

2012-01-01

Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP) markers. In addition, this study for the first time proposed a method to construct dominance relationship matrix using SNP markers and demonstrated it in detail. The proposed model was implemented to investigate the amounts of additive genetic, dominance and epistatic variations, and assessed the accuracy and unbiasedness of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1) a simple additive genetic model (MA), 2) a model including both additive and additive by additive epistatic genetic effects (MAE), 3) a model including both additive and dominance genetic effects (MAD), and 4) a full model including all three genetic components (MAED). Estimates of narrow-sense heritability were 0.397, 0.373, 0.379 and 0.357 for models MA, MAE, MAD and MAED, respectively. Estimated dominance variance and additive by additive epistatic variance accounted for 5.6% and 9.5% of the total phenotypic variance, respectively. Based on model MAED, the estimate of broad-sense heritability was 0.506. Reliabilities of genomic predicted breeding values for the animals without performance records were 28.5%, 28.8%, 29.2% and 29.5% for models MA, MAE, MAD and MAED, respectively. In addition, models including non-additive genetic effects improved unbiasedness of genomic predictions. PMID:23028912

Influence of outliers on accuracy estimation in genomic prediction in plant breeding.

PubMed

Estaghvirou, Sidi Boubacar Ould; Ogutu, Joseph O; Piepho, Hans-Peter

2014-10-01

Outliers often pose problems in analyses of data in plant breeding, but their influence on the performance of methods for estimating predictive accuracy in genomic prediction studies has not yet been evaluated. Here, we evaluate the influence of outliers on the performance of methods for accuracy estimation in genomic prediction studies using simulation. We simulated 1000 datasets for each of 10 scenarios to evaluate the influence of outliers on the performance of seven methods for estimating accuracy. These scenarios are defined by the number of genotypes, marker effect variance, and magnitude of outliers. To mimic outliers, we added to one observation in each simulated dataset, in turn, 5-, 8-, and 10-times the error SD used to simulate small and large phenotypic datasets. The effect of outliers on accuracy estimation was evaluated by comparing deviations in the estimated and true accuracies for datasets with and without outliers. Outliers adversely influenced accuracy estimation, more so at small values of genetic variance or number of genotypes. A method for estimating heritability and predictive accuracy in plant breeding and another used to estimate accuracy in animal breeding were the most accurate and resistant to outliers across all scenarios and are therefore preferable for accuracy estimation in genomic prediction studies. The performances of the other five methods that use cross-validation were less consistent and varied widely across scenarios. The computing time for the methods increased as the size of outliers and sample size increased and the genetic variance decreased. Copyright © 2014 Ould Estaghvirou et al.

Development and psychometric testing of the Adaptive Capacity Index, an instrument to measure adaptive capacity in individuals with advanced cancer.

PubMed

Olson, K; Rogers, W T; Cui, Y; Cree, M; Baracos, V; Rust, T; Mellott, I; Johnson, L; Macmillan, K; Bonville, N

2011-08-01

We have proposed that declines in adaptive capacity, defined as the ability to adapt to multiple stressors, may serve as an indicator of risk for fatigue. A comprehensive measure of adaptive capacity does not exist. In this paper we describe construction of an instrument to measure adaptive capacity, the Adaptive Capacity Index (ACI). Descriptive and psychometric. Six sites providing palliative care in Western Canada. ≥18 years old, diagnosed with advanced cancer, able to read and write English, Mini-Mental Status Exam score ≥22. Pilot study n=48; Main study n=225 stratified using the Edmonton Symptom Assessment Scale (ESAS) tiredness score (≥0 to ≤2 n=60; ≥3 to ≤6 n=108; ≥7 and ≤10 n=57). Following ethics approval, 17 experts in symptom management assisted with content validation and consenting individuals completed the Functional Assessment of Cancer Therapy-Fatigue (FACT-F), the Profile of Mood States-Vigor short form (POMS-Vsf), and the ACI. A research assistant collected demographic information and assigned an Eastern Cooperative Oncology Group (ECOG) score. Data were analyzed using descriptive and inferential statistics (i.e., exploratory factor analyses, correlation, multivariate analyses of variance, and multiple regression). Five 6-item ACI factors/subscales (Cognitive Function, Stamina/Muscle Endurance, Sleep Quality, Emotional Reactivity, and Social Interaction) were identified. The ACI-total scale and its subscales were internally consistent (Cronbach's alpha 0.76-0.89), and were significantly correlated with each other, and with each fatigue measure (Pearson's r ranging from -0.724 to 0.634). The ACI total score was sensitive to changes in the ESAS tiredness score. Stamina/Muscle Endurance, Cognitive Function, and Sleep Quality predicted 60.8% of the variance in FACT-F. Stamina/Muscle Endurance and Social Interaction predicted 36.8% of the variance in POMS-Vsf. Stamina/Muscle Endurance and Sleep Quality predicted 8% of the variance in ECOG. The ACI is reliable and has beginning evidence of validity. In future studies we will examine relationships between ACI subscale scores and subsequent increases in fatigue and explore linkages to physiological processes. We will also establish ACI norms for early and late stage cancers and explore variations in ACI subscale scores base on age or gender. Copyright © 2011 Elsevier Ltd. All rights reserved.

Measurement of academic entitlement.

PubMed

Miller, Brian K

2013-10-01

Members of Generation Y, or Millennials, have been accused of being lazy, whiny, pampered, and entitled, particularly in the college classroom. Using an equity theory framework, eight items from a measure of work entitlement were adapted to measure academic entitlement in a university setting in three independent samples. In Study 1 (n = 229), confirmatory factor analyses indicated good model fit to a unidimensional structure for the data. In Study 2 (n = 200), the questionnaire predicted unique variance in university satisfaction beyond two more general measures of dispositional entitlement. In Study 3 (n = 161), the measure predicted unique variance in perceptions of grade fairness beyond that which was predicted by another measure of academic entitlement. This analysis provides evidence of discriminant, convergent, incremental, concurrent criterion-related, and construct validity for the Academic Equity Preference Questionnaire.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Mishra, U.; Riley, W. J.

2015-01-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ~ 0.55-0.63). Current ESMs operate at coarse spatial scales (50-100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Mishra, U.; Riley, W. J.

2015-07-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data set with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ∼ 0.55-0.63). Current ESMs operate at coarse spatial scales (50-100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

DOE PAGES

Mishra, U.; Riley, W. J.

2015-07-02

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data setmore » with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ∼ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

DOE PAGES

Mishra, U.; Riley, W. J.

2015-01-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonablemore » fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ~ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

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

Mishra, U.; Riley, W. J.

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data setmore » with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ∼ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

Dopamine D1 Sensitivity in the Prefrontal Cortex Predicts General Cognitive Abilities and is Modulated by Working Memory Training

ERIC Educational Resources Information Center

Wass, Christopher; Pizzo, Alessandro; Sauce, Bruno; Kawasumi, Yushi; Sturzoiu, Tudor; Ree, Fred; Otto, Tim; Matzel, Louis D.

2013-01-01

A common source of variance (i.e., "general intelligence") underlies an individual's performance across diverse tests of cognitive ability, and evidence indicates that the processing efficacy of working memory may serve as one such source of common variance. One component of working memory, selective attention, has been reported to…

Prediction of bovine milk technological traits from mid-infrared spectroscopy analysis in dairy cows.

PubMed

Visentin, G; McDermott, A; McParland, S; Berry, D P; Kenny, O A; Brodkorb, A; Fenelon, M A; De Marchi, M

2015-09-01

Rapid, cost-effective monitoring of milk technological traits is a significant challenge for dairy industries specialized in cheese manufacturing. The objective of the present study was to investigate the ability of mid-infrared spectroscopy to predict rennet coagulation time, curd-firming time, curd firmness at 30 and 60min after rennet addition, heat coagulation time, casein micelle size, and pH in cow milk samples, and to quantify associations between these milk technological traits and conventional milk quality traits. Samples (n=713) were collected from 605 cows from multiple herds; the samples represented multiple breeds, stages of lactation, parities, and milking times. Reference analyses were undertaken in accordance with standardized methods, and mid-infrared spectra in the range of 900 to 5,000cm(-1) were available for all samples. Prediction models were developed using partial least squares regression, and prediction accuracy was based on both cross and external validation. The proportion of variance explained by the prediction models in external validation was greatest for pH (71%), followed by rennet coagulation time (55%) and milk heat coagulation time (46%). Models to predict curd firmness 60min from rennet addition and casein micelle size, however, were poor, explaining only 25 and 13%, respectively, of the total variance in each trait within external validation. On average, all prediction models tended to be unbiased. The linear regression coefficient of the reference value on the predicted value varied from 0.17 (casein micelle size regression model) to 0.83 (pH regression model) but all differed from 1. The ratio performance deviation of 1.07 (casein micelle size prediction model) to 1.79 (pH prediction model) for all prediction models in the external validation was <2, suggesting that none of the prediction models could be used for analytical purposes. With the exception of casein micelle size and curd firmness at 60min after rennet addition, the developed prediction models may be useful as a screening method, because the concordance correlation coefficient ranged from 0.63 (heat coagulation time prediction model) to 0.84 (pH prediction model) in the external validation. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Prediction of objectively measured physical activity and sedentariness among blue-collar workers using survey questionnaires.

PubMed

Gupta, Nidhi; Heiden, Marina; Mathiassen, Svend Erik; Holtermann, Andreas

2016-05-01

We aimed at developing and evaluating statistical models predicting objectively measured occupational time spent sedentary or in physical activity from self-reported information available in large epidemiological studies and surveys. Two-hundred-and-fourteen blue-collar workers responded to a questionnaire containing information about personal and work related variables, available in most large epidemiological studies and surveys. Workers also wore accelerometers for 1-4 days measuring time spent sedentary and in physical activity, defined as non-sedentary time. Least-squares linear regression models were developed, predicting objectively measured exposures from selected predictors in the questionnaire. A full prediction model based on age, gender, body mass index, job group, self-reported occupational physical activity (OPA), and self-reported occupational sedentary time (OST) explained 63% (R (2)adjusted) of the variance of both objectively measured time spent sedentary and in physical activity since these two exposures were complementary. Single-predictor models based only on self-reported information about either OPA or OST explained 21% and 38%, respectively, of the variance of the objectively measured exposures. Internal validation using bootstrapping suggested that the full and single-predictor models would show almost the same performance in new datasets as in that used for modelling. Both full and single-predictor models based on self-reported information typically available in most large epidemiological studies and surveys were able to predict objectively measured occupational time spent sedentary or in physical activity, with explained variances ranging from 21-63%.

Taylor's law and body size in exploited marine ecosystems.

PubMed

Cohen, Joel E; Plank, Michael J; Law, Richard

2012-12-01

Taylor's law (TL), which states that variance in population density is related to mean density via a power law, and density-mass allometry, which states that mean density is related to body mass via a power law, are two of the most widely observed patterns in ecology. Combining these two laws predicts that the variance in density is related to body mass via a power law (variance-mass allometry). Marine size spectra are known to exhibit density-mass allometry, but variance-mass allometry has not been investigated. We show that variance and body mass in unexploited size spectrum models are related by a power law, and that this leads to TL with an exponent slightly <2. These simulated relationships are disrupted less by balanced harvesting, in which fishing effort is spread across a wide range of body sizes, than by size-at-entry fishing, in which only fish above a certain size may legally be caught.

Taylor's law and body size in exploited marine ecosystems

PubMed Central

Cohen, Joel E; Plank, Michael J; Law, Richard

2012-01-01

Taylor's law (TL), which states that variance in population density is related to mean density via a power law, and density-mass allometry, which states that mean density is related to body mass via a power law, are two of the most widely observed patterns in ecology. Combining these two laws predicts that the variance in density is related to body mass via a power law (variance-mass allometry). Marine size spectra are known to exhibit density-mass allometry, but variance-mass allometry has not been investigated. We show that variance and body mass in unexploited size spectrum models are related by a power law, and that this leads to TL with an exponent slightly <2. These simulated relationships are disrupted less by balanced harvesting, in which fishing effort is spread across a wide range of body sizes, than by size-at-entry fishing, in which only fish above a certain size may legally be caught. PMID:23301181

Suitability of the HAM-Nat test and TMS module "basic medical-scientific understanding" for medical school selection

PubMed Central

Hissbach, Johanna; Feddersen, Lena; Sehner, Susanne; Hampe, Wolfgang

2012-01-01

Aims: Tests with natural-scientific content are predictive of the success in the first semesters of medical studies. Some universities in the German speaking countries use the ‘Test for medical studies’ (TMS) for student selection. One of its test modules, namely “medical and scientific comprehension”, measures the ability for deductive reasoning. In contrast, the Hamburg Assessment Test for Medicine, Natural Sciences (HAM-Nat) evaluates knowledge in natural sciences. In this study the predictive power of the HAM-Nat test will be compared to that of the NatDenk test, which is similar to the TMS module “medical and scientific comprehension” in content and structure. Methods: 162 medical school beginners volunteered to complete either the HAM-Nat (N=77) or the NatDenk test (N=85) in 2007. Until spring 2011, 84.2% of these successfully completed the first part of the medical state examination in Hamburg. Via different logistic regression models we tested the predictive power of high school grade point average (GPA or “Abiturnote”) and the test results (HAM-Nat and NatDenk) with regard to the study success criterion “first part of the medical state examination passed successfully up to the end of the 7th semester” (Success7Sem). The Odds Ratios (OR) for study success are reported. Results: For both test groups a significant correlation existed between test results and study success (HAM-Nat: OR=2.07; NatDenk: OR=2.58). If both admission criteria are estimated in one model, the main effects (GPA: OR=2.45; test: OR=2.32) and their interaction effect (OR=1.80) are significant in the HAM-Nat test group, whereas in the NatDenk test group only the test result (OR=2.21) significantly contributes to the variance explained. Conclusions: On their own both HAM-Nat and NatDenk have predictive power for study success, but only the HAM-Nat explains additional variance if combined with GPA. The selection according to HAM-Nat and GPA has under the current circumstances of medical school selection (many good applicants and only a limited number of available spaces) the highest predictive power of all models. PMID:23255967

Examination of psychosocial predictors of Virginia pharmacists' intention to utilize a prescription drug monitoring program using the theory of planned behavior.

PubMed

Gavaza, Paul; Fleming, Marc; Barner, Jamie C

2014-01-01

Little is known about the main drivers of pharmacists' intention to utilize prescription drug monitoring programs (PDMPs) when making care decisions and the actual contribution of these factors in explaining intention and behavior. This study examined what theory of planned behavior (TPB) model constructs (i.e., attitude, subjective norm [SN], perceived behavioral control [PBC]), past utilization behavior (PUB) and perceived moral obligation (PMO) were significant predictors of Virginia community pharmacists' intention to utilize a PDMP. A cover letter with a link to a 28-item online survey was e-mailed to 600 members of the Virginia Pharmacists Association. Multiple regression analyses were used to determine the association between pharmacists' intention to utilize the PDMP database and attitude, SN, PBC, PUB and PMO. Ninety-seven usable responses were received, for a response rate of 16.2%. A majority of the respondents were Caucasian (96.4%), female (50.5%), working in independent community pharmacies (60.4%) with an average age of 49.5 ± 13.4 years. Overall, pharmacists intended to utilize a PDMP (mean = 5.3 ± 4.6; possible range: -9 to 9), had a positive attitude toward utilizing PDMP (mean = 6.3 ± 5.3; possible range: -12 to 12), perceived that others wanted them to utilize a PDMP (SN score = 3.7 ± 2.4; range: -6 to 6), and believed that they had control over utilization behavior (PBC score = 4.5 ± 4.0; range: -9 to 9). Attitude (β = 0.723, P < 0.001), SN (β = 0.230, P = 0.014) and PBC (β = -0.215, P = 0.026) significantly predicted pharmacists' intent, accounting for 56.7% of the variance in intention to utilize the PDMP database (P < 0.001). The addition of PMO (P < 0.001) significantly contributed to explaining the variance in intention but PUB did not. Members of the Virginia Pharmacists Association who responded to the survey showed a strong positive intent to utilize PDMP database. Pharmacists' attitudes, subjective norm, perceived behavioral control and perceived moral obligation were significant predictors of intention but past utilization behavior was not. The TPB is a useful theoretical framework when predicting PDMP utilization behavior of community pharmacists, accounting for 56.7% of the variance in intention. Copyright © 2014 Elsevier Inc. All rights reserved.

Predictors of physical activity in persons with mental illness: Testing a social cognitive model.

PubMed

Zechner, Michelle R; Gill, Kenneth J

2016-12-01

This study examined whether the social cognitive theory (SCT) model can be used to explain the variance in physical exercise among persons with serious mental illnesses. A cross-sectional, correlational design was employed. Participants from community mental health centers and supported housing programs (N = 120) completed 9 measures on exercise, social support, self-efficacy, outcome expectations, barriers, and goal-setting. Hierarchical regression tested the relationship between self-report physical activity and SCT determinants while controlling for personal characteristics. The model explained 25% of the variance in exercise. Personal characteristics explained 18% of the variance in physical activity, SCT variables of social support, self-efficacy, outcome expectations, barriers, and goals were entered simultaneously, and they added an r2 change value of .07. Gender (β = -.316, p = .001) and Brief Symptom Inventory Depression subscale (β = -2.08, p < .040) contributed significantly to the prediction of exercise. In a separate stepwise multiple regression, we entered only SCT variables as potential predictors of exercise. Goal-setting was the single significant predictor, F(1, 118) = 13.59, p < .01), r2 = .10. SCT shows promise as an explanatory model of exercise in persons with mental illnesses. Goal-setting practices, self-efficacy, outcome expectations and social support from friends for exercise should be encouraged by psychiatric rehabilitation practitioners. People with more depressive symptoms and women exercise less. More work is needed on theoretical exploration of predictors of exercise. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

An exploration of the role of subordinate affect in leader evaluations.

PubMed

Martinko, Mark J; Mackey, Jeremy D; Moss, Sherry E; Harvey, Paul; McAllister, Charn P; Brees, Jeremy R

2018-03-26

Leadership research has been encumbered by a proliferation of constructs and measures, despite little evidence that each is sufficiently conceptually and operationally distinct from the others. We draw from research on subordinates' implicit theories of leader behavior, behaviorally anchored rating scales, and decision making to argue that leader affect (i.e., the degree to which subordinates have positive and negative feelings about their supervisors) underlies the common variance shared by many leadership measures. To explore this possibility, we developed and validated measures of positive and negative leader affect (i.e., the Leader Affect Questionnaires; LAQs). We conducted 10 studies to develop the five-item positive and negative LAQs and to examine their convergent, discriminant, predictive, and criterion-related validity. We conclude that a) the LAQs provide highly reliable and valid tools for assessing subordinates' evaluations of their leaders; b) there is significant overlap between existing leadership measures, and a large proportion of this overlap is a function of the affect captured by the LAQs; c) when the LAQs are used as control variables, in most cases, they reduce the strength of relationships between leadership measures and other variables; d) the LAQs account for significant variance in outcomes beyond that explained by other leadership measures; and e) there is a considerable amount of unexplained variance between leadership measures that the LAQs do not capture. Research suggestions are provided and the implications of our results are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Development of design and analysis methodology for composite bolted joints

NASA Astrophysics Data System (ADS)

Grant, Peter; Sawicki, Adam

1991-05-01

This paper summarizes work performed to develop composite joint design methodology for use on rotorcraft primary structure, determine joint characteristics which affect joint bearing and bypass strength, and develop analytical methods for predicting the effects of such characteristics in structural joints. Experimental results have shown that bearing-bypass interaction allowables cannot be defined using a single continuous function due to variance of failure modes for different bearing-bypass ratios. Hole wear effects can be significant at moderate stress levels and should be considered in the development of bearing allowables. A computer program has been developed and has successfully predicted bearing-bypass interaction effects for the (0/+/-45/90) family of laminates using filled hole and unnotched test data.

Reducing voluntary, avoidable turnover through selection.

PubMed

Barrick, Murray R; Zimmerman, Ryan D

2005-01-01

The authors investigated the efficacy of several variables used to predict voluntary, organizationally avoidable turnover even before the employee is hired. Analyses conducted on applicant data collected in 2 separate organizations (N = 445) confirmed that biodata, clear-purpose attitudes and intentions, and disguised-purpose dispositional retention scales predicted voluntary, avoidable turnover (rs ranged from -.16 to -.22, R = .37, adjusted R = .33). Results also revealed that biodata scales and disguised-purpose retention scales added incremental validity, whereas clear-purpose retention scales did not explain significant incremental variance in turnover beyond what was explained by biodata and disguised-purpose scales. Furthermore, disparate impact (subgroup differences on race, sex, and age) was consistently small (average d = 0.12 when the majority group scored higher than the minority group).

Risk Adjustment for a Children's Capitation Rate

PubMed Central

Newhouse, Joseph P.; Sloss, Elizabeth M.; Manning, Willard G.; Keeler, Emmett B.

1993-01-01

Few capitation arrangements vary premiums by a child's health characteristics, yielding an incentive to discriminate against children with predictably high expenditures from chronic diseases. In this article, we explore risk adjusters for the 35 percent of the variance in annual outpatient expenditure we find to be potentially predictable. Demographic factors such as age and gender only explain 5 percent of such variance; health status measures explain 25 percent, prior use and health status measures together explain 65 to 70 percent. The profit from risk selection falls less than proportionately with improved ability to adjust for risk. Partial capitation rates may be necessary to mitigate skimming and dumping. PMID:10133708