Indication Of Bias Research Articles

Social cognition in patients with first episode of psychosis in remission.

Aim:The present study aimed to compare the social cognition (SC) deficits in patients with first-episode psychosis (FEP) and healthy controls and evaluate the association of SC deficits with socio-occupational functioning, insight, quality of life, and stigma.Methods:This study included 30 patients with FEP in remission phase and 26 healthy controls matched for age, gender, education, and intelligent quotient. SC was assessed on the domains of theory of mind (ToM), social perception, and attributional bias.Results:Compared to healthy controls, patients with FEP had significantly higher deficits in the domains of second-order ToM (unpaired t = 4.447, P < 0.001) and Faux Pas Composite Index (unpaired t = 2.824, P = 0.007). In the correlation analysis, higher age of patients with FEP was significantly associated with more externalizing bias (Pearson's correlation coefficient = 0.38, P = 0.039) and those with lower level of education had more social cognitive deficits in the domains of Faux Pas Composite Index (Pearson's correlation coefficient = 0.43, P = 0.018), Social Perception Index (Pearson's correlation coefficient = 0.38, P = 0.04), and Nonsocial Perception Index (Pearson's correlation coefficient = 0.5, P = 0.005). Duration of untreated psychosis was associated with higher deficits in the first-order ToM (Pearson's correlation coefficient = −0.38, P = 0.04) and Externalizing Bias Index (Pearson's correlation coefficient = −0.49, P = 0.006). Longer duration of treatment was associated with higher impairment in first-order ToM index (Pearson's correlation coefficient = −0.42, P = 0.02). General psychopathology and total Positive and Negative Syndrome Scale total score correlated significantly with externalizing bias, with a higher level of psychopathology associated with more severe deficits in this domain. There was no correlation of SC with the quality of life, cognitive insight, and stigma (except for occasional correlation of stereotype endorsement and externalizing bias).Conclusion:The present study suggests that compared to healthy controls, patients with FEP have impairment in the domains of second-order ToM and Faux Pas Composite Index. However, social cognitive deficits have only a few correlations with various psychosocial outcomes of FEP.

Reliability of the Scapula Reposition Test in Subjects with Rotator Cuff Tendinopathy and Scapular Dyskinesis

The Scapula Reposition Test (SRT) is proposed to determine if a relationship exists between scapular dyskinesis and shoulder pathology. The purpose of this study was to evaluate intra-rater and inter-rater reliability of the SRT in subjects with rotator cuff tendinopathy and scapular dyskinesis. In addition, we compared subjective strength findings from the test to an objective measure made by dynamometry. The SRT was independently and randomly performed by two physical therapists in 42 subjects. The percent agreement, Cohen’s kappa (κ), maximum attainable κ, prevalence and bias indexes, and prevalence-adjusted-bias-adjusted kappa were used as intra- and inter-rater reliability estimates. Finally, the point-biserial correlation coefficient (rpb) was used for correlation analysis of objective and subjective strength findings. A moderate intra-rater (κ = 0.43; CI 95%, 0.14 to 0.73; p = 0.004) and poor inter-rater (κ = 0.08; CI 95%, −0.22 to 0.38; p = 0.61) agreement was found. Subjective strength changes during SRT and dynamometry were poorly correlated (rpb = 0.137; CI 95%, −0.175 to 0.423; p = 0.389). The SRT cannot be recommended for clinical practice. More studies evaluating its reliability are needed as well as further research on the capability of a rater to manually detect strength changes.

A NON-DESTRUCTIVE METHOD FOR ESTIMATING LEAF AREA OF Ceiba glaziovii (Kuntze) K. Schum.

The determination of leaf area is of fundamental importance in studies involving ecological and ecophysiological aspects of forest species. The objective of this research was to adjust an equation to determine the leaf area of Ceiba glaziovii as a function of linear measurements of leaves. Six hundred healthy leaf limbs were collected in different matrices, with different shapes and sizes, in the Mata do Pau-Ferro State Park, Areia, Paraíba state, Northeast Brazil. The maximum length (L), maximum width (W), product between length and width (L.W), and leaf area of the leaf limbs were calculated. The regression models used to construct equations were: linear, linear without intercept, quadratic, cubic, power and exponential. The criteria for choosing the best equation were based on the coefficient of determination (R²), Akaike information criterion (AIC), root mean square error (RMSE), Willmott concordance index (d) and BIAS index. All the proposed equations satisfactorily estimate the leaf area of C. glaziovii, due to their high determination coefficients (R² ≥ 0.851). The linear model without intercept, using the product between length and width (L.W), presented the best criteria to estimate the leaf area of the species, using the equation 0.4549*LW.

Evaluations on gridded precipitation products spanning more than half a century over the Tibetan Plateau and its surroundings

Long-term precipitation data play significant roles in hydrological applications and climate change studies. In this study three gridded precipitation products (Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources, APHRODITE; Climate Hazards Group InfraRed Precipitation with Station data, CHIRPS; and Precipitation Estimation from Remotely sensed Information using Artificial Neural Networks-Climate Data Record, PERSIANN-CDR) with the spatial resolution of 0.25° were evaluated using rain gauge data at the daily, monthly and annual scales over the Tibetan Plateau and its surrounding areas (TP). R2, bias, RMSE and MAE were adopted to assess precipitation amount; indices including the probability of detection (POD), false alarm ratio (FAR), critical success index (CSI) and frequency bias index (FBI) were used to evaluate gridded products’ ability to detect precipitation occurrences. We found that: (1) APHRODITE outperformed CHIRPS and PERSIANN-CDR against observations at the annual scale with the highest R2 (~0.93), the lowest MAE (~67 mm/year) and RMSE (~116 mm/year), and APHRODITE also showed better performance in distinguishing rain/no rain events with the highest POD (~0.9) and CSI (>0.6), the lowest FAR (~0.35), followed by PERSAINN-CDR and CHIRPS; (2) CHIRPS performed nearly to APHRODITE in precipitation amount with R2 around 0.8 while the lowest POD (<0.4) implied the shortage for CHIRPS in detecting rain/no rain conditions; (3) in spite of the lowest agreement with gauge measurements with the largest bias (~25%), PERSIANN-CDR had a relatively higher mean POD (>0.5), indicating that PERSIANN-CDR had better potential of detecting rainfall occurrences than CHIRPS but tended to overestimate precipitation; (4) generally, PERSIANN-CDR overestimated the precipitation greater than CHIRPS and APHRODITE data at monthly scale; and (5) the three products correlated well with each other in the interior, southern and eastern regions of TP but there were still some significant differences along the borders and surroundings of the TP by inter-comparisons. Finally, we recommended APHRODITE for climate change study for its high accuracy and long-time series, CHIRPS and PERSIANN-CDR could also be considered after correction.

What’s about the Calibration between Confidence and Accuracy? Findings in Probabilistic Problems from Italy and Spain

This paper reports some experiments on probabilistic reasoning designed to investigate the impact of the probabilistic problem presentation format (verbal-numerical and graphical-pictorial) on subjects’ confidence in the correctness of their performance, other than the calibration between confidence and accuracy. To understand the potential effect of the format, these dimensions were assessed by monitoring contextual and individual variables: time pressure, numerical and visuospatial abilities, statistical anxiety and attitudes towards statistics. The participants included 257 Psychology students without statistical knowledge, recruited from Italian and Spanish universities, who fulfilled self-report validated measures. The students expressed their retrospective judgments of confidence item-by-item in relation to each probabilistic problem. This approach enabled the computation of two measures of calibration (the Bias Index - the Confidence-Judgment Accuracy Quotient). The results indicated that the problem presentation format did not exert a significant main effect on confidence, with the exception of when the interaction between the format and one subscale of the attitudes towards the statistics test was considered. The Bias Index, however, was significantly related to the interaction between format and time pressure. The study offers a point of reflection in relation to the potential effect exerted by the problem format and time constraint in calibration.

Qualification and Quantification on Viewpoint Biases in Large Scale Image Datasets for General Object Recognition

While recognizing an image taken from an arbitrary angle in a real environment, it may be challenging to obtain a good recognition result on occasion. That is, the recognition accuracy is affected by changing the viewpoint (object viewing direction). This phenomenon could come from the fact that people photograph target objects on well explainable aspect. It has been known empirically that the recognition rate varies depending on the viewpoint so far, but this topic remains underdeveloped. Therefore, in this research, we aim to clarify and visualize the existence of viewpoint biases in existing large object recognition image datasets. We also quantify the viewpoint biases by a definition of viewpoint bias index.

Estimation of leaf area of Erythroxylum citrifolium from linear leaf dimensions

Erythroxylum citrifolium is a neotropical plant species recorded in all regions of Brazil. Determining leaf area is of fundamental importance to studies related to plant propagation and growth. The objective was to obtain an equation to estimate the leaf area of E. citrifolium from linear dimensions of the leaf blade (length and width). A total of 200 leaf blades were collected in Parque Estadual Mata do Pau-Ferro in the municipality of Areia, state of Paraíba, Northeast Brazil. The models evaluated were: linear, linear without intercept, quadratic, cubic, power and exponential. The best model was determined by the criteria of: high coefficient of determination (R²), low root mean square error (RMSE), low Akaike information criterion (AIC), high Willmott concordance index (d) and a BIAS index close to zero. All of the models constructed satisfactorily estimated the leaf area of E. citrifolium, with coefficients of determination above 0.9050, but the power model using the product between length and width (L*W) ŷ = 0.5966 * LW1.0181 was the best, with the highest values of R² and d, low values of RMSE and AIC, and a BIAS index closest to zero.

Performance Assessment of Sub-Daily and Daily Precipitation Estimates Derived from GPM and GSMaP Products over an Arid Environment

Precipitation is a critical variable for comprehending various climate-related research, such as water resources management, flash flood monitoring and forecasting, climatic analyses, and hydrogeological studies, etc. Here, our objective was to evaluate the rainfall estimates obtained from Global Precipitation Mission (GPM), and Global Satellite Mapping of Precipitation (GSMaP) constellation over an arid environment like the Sultanate of Oman that is characterized by a complex topography and extremely variable rainfall patterns. Global Satellite-based Precipitation Estimates (GSPEs) can provide wide coverage and high spatial and temporal resolutions, but evaluating their accuracy is a mandatory step before involving them in different hydrological applications. In this paper, the reliability of the Integrated Multi-satellitE Retrievals for the GPM (IMERG) V04 and GSMaP V06 products were evaluated using the reference in-situ rain gauges at sub-daily (e.g., 6, 12, and 18 h) and daily time scales during the period of March 2014–December 2016. A set of continuous difference statistical indices (e.g., mean absolute difference, root mean square error, mean difference, and unconditional bias), and categorical metrics (e.g., probability of detection, critical success index, false alarm ratio, and frequency bias index) were used to evaluate recorded precipitation occurrences. The results showed that the five GSPEs could generally delineate the spatial and temporal patterns of rainfall while they might have over- and under-estimations of in-situ gauge measurements. The overall quality of the GSMaP runs was superior to the IMERG products; however, it also encountered an exaggeration in case of light rain and an underestimation for heavy rain. The effects of the gauge calibration algorithm (GCA) used in the final IMERG (IMERG-F) were investigated by comparison with early and late runs. The IMERG-F V04 product did not show a significant improvement over the early (i.e., after 4 h of rainfall observations) and late (i.e., after 12 h of rainfall observations) products. The results indicated that GCA could not reduce the missed precipitation records considerably.

Assessment of hydrological regionalization methodologies for the upper Jaguari River basin

Water resources management is meant to solve problems caused by the intensive use of this resource which is the consequence of economic and population growth. Water resources management is also responsible for preserving hydrological, biological and chemical functions of ecosystems, as well as ensuring that this resource will be maintained with adequate supply for future generations. In Brazil, a country with continental dimensions, streamflow gauge coverage is far from satisfactory. Therefore, the hydrological regionalization techniques are an option to estimate hydrological information in regions with few or no data. This methodology is based on the spatial similarity of functions, variables and parameters that tolerate this transference. The number of regionalization models and the need for ease of access to hydrological data transformed comparative studies of streamflow regionalization methodologies into an important topic of hydrology in Brazil. For this reason, the objective of this paper is to assess the models settled by Liazi et al. (1988), IGAM (2012) and Wolff et al. (2014) related to the variables Q7,10, Q90, Q95 and Q‾ in the upper Jaguari River basin, which is located between Minas Gerais and São Paulo States, and represents an important affluent to the Cantareira System. Firstly, Q7,10, Q90, Q95 and Q‾ were calculated using the historical flow data from five fluviometric stations located in Jaguari River basin. Then, these same variables were estimated using the regionalization methodologies proposed by Liazi et al. (1988), IGAM (2012) and Wolff et al. (2014). In order to determine the best hydrological regionalization method for the upper Jaguari River basin, the flow rates results calculated with the historical series were compared to those estimated by the models. Liazi et al. (1988) presented the best performance when compared to the other two methods. Its behavior was classified as very good by the index of agreement (d), the Nash-Sutcliffe efficiency (NSE) and the coefficient of determination (R2). IGAM (2012) exhibited an unsatisfactory fit for the statistical indicators of NSE and PBIAS. On the other hand, this method was classified as very good when the coefficient of determination (R2) was analyzed. The proposal of hydrological regionalization of Wolff et al. (2014) presented an adjustment, classified by the index of agreement (d), Nash-Sutcliffe efficiency (NSE), percentage bias (PBIAS), and coefficient of determination (R2) as unsatisfactory, in general. The graphical behavior, however, demonstrated a good potential for future use of this model. In conclusion, it is recommended to apply similar comparative studies in other important sub-basins located between Minas Gerais and São Paulo States in Brazil to corroborate or not with the presented results.

Quantifying gender bias

Stem Workforce Gender biases persist in academia, but no tool that quantifies the extent of these biases currently exists. Tran et al. developed and validated the Perceived Subtle Gender Bias Index (PSGBI), designed to quantify women's perceptions of subtle biases within academia. The PSGBI contains four subscales: perceived gender inequity, collegiality, mentorship, and institutional support. The PSGBI was able to differentiate the higher perceptions of subtle gender biases by academic rank, tenured women, and women in men-dominated contexts, that is, associate and full professors perceived more inequality and biases relative to assistant professors. Moving forward, the PSGBI can provide women academics and their allies with data for further discussing gender bias as well as a set of events and experiences to understand where and when biases may be experienced. Psychol. Women Q. 10.1177/0361684319877199 (2019).

Comment on "Quantifying the informational value of classification images": A miscomputation of the infoVal metric.

Brinkman et al. (2019) recently introduced an innovative metric-infoVal-to assess the informational value of classification images (CIs) relative to a random distribution. Although this measure constitutes a valuable tool to distinguish random from nonrandom CIs, we identified two noteworthy discrepancies between the mathematical formalization of the infoVal metric and the authors' computation. Specifically, the computation was based on the one norm instead of the Euclidean norm, and the k constant was omitted in the denominator of the ratio that produces infoVal. Accordingly, the simulations and experimental results reported by Brinkman et al. do not build on the correct infoVal computation but on a biased index. Importantly, this discrepancy in the computation affects the statistical power and Type I and error rate of the metric. Here we clarify the nature of the discrepancies in the computation and run Brinkman et al.'s Simulation 1 anew with the correct values, to illustrate their consequences. Overall, we found that relying on the miscomputed infoVal metric can lead to misguided conclusions, and we urge researchers to use the correct values.

Signal-detection analysis of the WMS faces subtest: Results in amyotrophic lateral sclerosis patients

About 30% of patients with amyotrophic lateral sclerosis (ALS) suffer from cognitive impairment and 10–15% suffer from frontotemporal dementia (FTD). Due to the patients’ reduced motor function, a neuropsychological assessment with a low motor demand can be an advantage when evaluating patients, aiding its application. The present work has studied the usefulness of the Faces subtest of the Wechsler Memory Scale in 42 patients with ALS and 42 healthy volunteers applying Holdnack’s Two-High Threshold model. The ALS group performed significantly worse in immediate and delayed discriminability. With respect to the presence of cognitive impairment, it seemed to be independent of the indexes proposed by Holdnack and Delis. On the other hand, motor problems were associated with delayed recognition while behavior alterations were linked to problems with delayed discriminability. ALS patients do not express differences in the bias index, in line with other types of previously studied pathologies.

Perceived Subtle Gender Bias Index: Development and Validation for Use in Academia

In this article, we present the development and validation of the Perceived Subtle Gender Bias Index. Given the inherent difficulty in identifying and measuring the perceptions of subtle gender biases, this index provides researchers and interventionists with a tool that does not require participants to identify/label an event as a gender bias incident. We used a mixed method and constructivist approach that prioritized and privileged the voices and experiences of women in science, technology, engineering, and mathematics (STEM). The current article describes two studies: (1) index development and (2) index refinement and validation, using a national survey of women academics ( N = 882). Findings support a four-subscale structure, including perceived gender inequity, collegiality, mentorship, and institutional support. Methods and analyses support face, convergent, discriminant, and predictive validity for the use of the index among academic faculty women. Additional online materials for this article are available on PWQ’s website at http://journals.sagepub.com/doi/suppl/10.1177/0361684319877199

Brain responses and approach bias to social alcohol cues and their association with drinking in a social setting in young adult males.

Alcohol is mainly consumed in social settings, in which people often adapt their drinking behaviour to that of others, also called imitation of drinking. Yet, it remains unclear what drives this drinking in a social setting. In this study, we expected to see stronger brain and behavioural responses to social compared to non‐social alcohol cues, and these responses to be associated with drinking in a social setting. The sample consisted of 153 beer‐drinking males, aged 18–25 years. Brain responses to social alcohol cues were measured during an alcohol cue‐exposure task performed in an fMRI scanner. Behavioural responses to social alcohol cues were measured using a stimulus‐response compatibility task, providing an index of approach bias towards these cues. Drinking in a social setting was measured in a laboratory mimicking a bar environment. Specific brain responses to social alcohol cues were observed in the bilateral superior temporal sulcus and the left inferior parietal lobe. There was no approach bias towards social alcohol cues specifically; however, we did find an approach bias towards alcohol (versus soda) cues in general. Brain responses and approach bias towards social alcohol cues were unrelated and not associated with actual drinking. Thus, we found no support for a relation between drinking in a social setting on the one hand, and brain cue‐reactivity or behavioural approach biases to social alcohol cues on the other hand. This suggests that, in contrast to our hypothesis, drinking in a social setting may not be driven by brain or behavioural responses to social alcohol cues.

Investigation on the Potential to Integrate Different Artificial Intelligence Models with Metaheuristic Algorithms for Improving River Suspended Sediment Predictions

Suspended sediment load (SLL) prediction is a significant field in hydrology and hydraulic sciences, as sedimentation processes change the soil quality. Although the adaptive neuro fuzzy system (ANFIS) and multilayer feed-forward neural network (MFNN) have been widely used to simulate hydrological variables, improving the accuracy of the above models is an important issue for hydrologists. In this article, the ANFIS and MFNN models were improved by the bat algorithm (BA) and weed algorithm (WA). Thus, the current paper introduces improved ANFIS and MFNN models: ANFIS–BA, ANFIS–WA, MFNN–BA, and MFNN–WA. The models were validated by applying river discharge, rainfall, and monthly suspended sediment load (SSL) for the Atrek basin in Iran. In addition, seven input groups were used to predict monthly SSL. The best models were identified through root-mean-square error (RMSE), Nash–Sutcliff efficiency (NSE), standard deviation ratio (RSR), percent bias (PBIAS) indices, and uncertainty analysis. For the ANFIS–BA model, RMSE and RSR varied from 1.5 to 2.5 ton/d and from 5% to 25%, respectively. In addition, a variation range of NSE was between very good and good performance (0. 75 to 0.85 and 0.85 to 1). The uncertainty analysis showed that the ANFIS–BA had more reliable performance compared to other models. Thus, the ANFIS–BA model has high potential for predicting SSL.

Determining the Parameters of the Ångström‐Prescott Model for Estimating Solar Radiation in Different Regions of China: Calibration and Modeling

AbstractThe Ångström‐Prescott model (referred to as the A‐P model) is one of the most accurate and widely used models for estimating global solar radiation (Rs). In the absence of Rs measurements and given the regional discrepancy of model parameters, it is crucial to increase the availability of these parameters and the applicability of parameter‐predicted models in different regions. In this study, we evaluated and compared the applicability and performance of the calibrated model and eight predictive models in terms of A‐P model parameters, using daily Rs and meteorological data from 105 radiation stations in seven natural geographic zones in China. These models were evaluated based on their coefficient of determination (R2), root mean square error, Nash‐Sutcliffe efficiency coefficients, percent bias, and global performance indexes. Results indicated that altitude was the main factor determining the Ångström‐Prescott parameters in most regions. All models performed well, with acceptable accuracy across the whole country; however, their performances varied among regions. The best performing predictive models for the northeast region (Zone 1), north China (Zone 2), central China (Zone 3), south China (Zone 4), Inner Mongolia (Zone 5), northwest region (Zone 6), and Qinghai‐Tibet region (Zone 7) were obtained: These were Models 6, 1, 7, 3, 6, 1, and 7, respectively. The present results support the application of these predictive models for the estimation of daily global Rs in the corresponding regions of China, where measured Rs data are not available, and possibly in other regions with a similar climate.

Systematic Comparisons of Positively Selected Genes between Gossypium arboreum and Gossypium raimondii Genomes

Background:Studies of Positively Selected Genes (PSGs) in microorganisms and mammals have provided insights into the dynamics of genome evolution and the genetic basis of differences between species by using whole genome-wide scans. Systematic investigations and comparisons of PSGs in plants, however, are still limited.Objective:A systematic comparison of PSGs between the genomes of two cotton species, Gossypium arboreum (G. arboreum) and G. raimondii, will give the key answer for revealing molecular evolutionary differences in plants.Methods:Genome sequences of G. arboreum and G. raimondii were compared, including Whole Genome Duplication (WGD) events and genomic features such as gene number, gene length, codon bias index, evolutionary rate, number of expressed genes, and retention of duplicated copies.Results:Unlike the PSGs in G. raimondii, G. arboreum comprised more PSGs, smaller gene size and fewer expressed gene. In addition, the PSGs evolved at a higher rate of synonymous substitutions, but were subjected to lower selection pressure. The PSGs in G. arboreum were also retained with a lower number of duplicate gene copies than G. raimondii after a single WGD event involving Gossypium.Conclusion:These data indicate that PSGs in G. arboreum and G. raimondii differ not only in Ka/Ks, but also in their evolutionary, structural, and expression properties, indicating that divergence of G. arboreum and G. raimondii was associated with differences in PSGs in terms of evolutionary rates, gene length, expression patterns, and WGD retention in Gossypium.

Social anxiety and attentional bias variability: electrophysiological evidence of attentional control deficits.

Attentional control has an important role in attentional bias in social anxiety. This study aimed to investigate whether attentional bias in social anxiety was caused by attentional control deficit. Event-related potentials and behavioural attentional bias index (trial-level attentional bias variability) were recorded as participants completed the dot-probe task. The behaviour result showed that compared with the low socially anxious individuals, the high socially anxious individuals had a marginally higher score of attentional bias variability. For event-related potentials results, target-locked frontocentral N2 amplitude was significantly larger under the incongruent condition than the congruent condition in the low socially anxious group, whereas there was no significant difference between these two conditions in the high socially anxious group. The low socially anxious group also exhibited reduced target-locked P2 amplitude from the congruent condition to the incongruent condition. Our findings provide electrophysiological evidence of attentional control dysregulation in socially anxious individuals, which contributes to modifying social anxiety-related attentional bias.

DYNAMICS OF HEAT FLUXES BY BOWEN AND MATMNXFLX AND NOAH FLDAS PRODUCTS IN THE PANTANAL OF MATO GROSSO.

This paper aimed to analyze the dynamics of the energy budget components: latent heat flux (LE), sensible heat flux (H) and soil heat flux (G), in the Mato Grosso Pantanal. The estimates of LE, H, and G were obtained by the Bowen ratio methods, using data from the micrometeorological tower located in the Baía das Pedras Park of SESC-Pantanal Ecological Resort, for the years 2011 to 2013. The normality of the variables Rn, LE, H and G, were tested by Kolmogorov-Smirnov test at 5% significance, and the seasonal differences of the fluxes were verified by the KruskalWallis test, α = 0.05. LE and H data from the remote sensing products MATMNXFLX and FLDAS_NOAH of the MERRA model was also acquired, and their comparison with the tower data was performed by the statistics of Spearman correlation (r), Mean Absolute Error (MAE), Root Mean Squared Erro (RMSE), bias, and Willmott's Concordance Index (d). It was observed that most of the available energy is used for evapotranspiration (latent heat), followed by sensible heat and soil heat flux. In the rainy season there is an increase in the partition of LE and G and reduction of H. Only the estimates of LE of MATMNXFLX and FLDAS_NOAH products correlate with the data observed in the meteorological tower. It is concluded that the energy partitions have a seasonal behavior and that the MATMNXFLX and FLDAS_NOAH products, after being calibrated, can be used to estimate LE in the Mato Grosso Pantanal.

Delay Discounting as a Transdiagnostic Process in Psychiatric Disorders

Delay discounting is a behavioral economic index of impulsive preferences for smaller-immediate or larger-delayed rewards that is argued to be a transdiagnostic process across health conditions. Studies suggest some psychiatric disorders are associated with differences in discounting compared with controls, but null findings have also been reported. To conduct a meta-analysis of the published literature on delay discounting in people with psychiatric disorders. PubMed, MEDLINE, PsycInfo, Embase, and Web of Science databases were searched through December 10, 2018. The psychiatric keywords used were based on DSM-IV or DSM-5 diagnostic categories. Collected data were analyzed from December 10, 2018, through June 1, 2019. Following a preregistered Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) protocol, 2 independent raters reviewed titles, abstracts, and full-text articles. English-language articles comparing monetary delay discounting between participants with psychiatric disorders and controls were included. Hedges g effect sizes were computed and random-effects models were used for all analyses. Heterogeneity statistics, one-study-removed analyses, and publication bias indices were also examined. Categorical comparisons of delay discounting between a psychiatric group and a control group. The sample included 57 effect sizes from 43 studies across 8 diagnostic categories. Significantly steeper discounting for individuals with a psychiatric disorder compared with controls was observed for major depressive disorder (Hedges g = 0.37; P = .002; k = 7), schizophrenia (Hedges g = 0.46; P = .004; k = 12), borderline personality disorder (Hedges g = 0.60; P < .001; k = 8), bipolar disorder (Hedges g = 0.68; P < .001; k = 4), bulimia nervosa (Hedges g = 0.41; P = .001; k = 4), and binge-eating disorder (Hedges g = 0.34; P = .001; k = 7). In contrast, anorexia nervosa exhibited statistically significantly shallower discounting (Hedges g = -0.30; P < .001; k = 10). Modest evidence of publication bias was indicated by a statistically significant Egger test for schizophrenia and at the aggregate level across studies. Results of this study appear to provide empirical support for delay discounting as a transdiagnostic process across most of the psychiatric disorders examined; the literature search also revealed limited studies in some disorders, notably posttraumatic stress disorder, which is a priority area for research.