Social interaction anxiety and depression symptoms are differentially related in men and women.

Social anxiety disorder (SAD) and major depressive disorder (MDD) are highly comorbid with each other, and comorbidity exacerbates distress and impairment. The prevalence of comorbid depression is higher in women with SAD than in men with SAD, but this is based on global depression scores and cannot speak to heterogeneous individual depression symptoms. The current study bridges this gap by examining gender differences in the relationship between social interaction anxiety and individual depression symptoms. 165 community adults (113 women, 52 men) were included in a series of bootstrapped moderation analyses to examine the main and interaction effects of social interaction anxiety and gender on total depression and individual depressive symptom scores while controlling for age and racial/ethnic background. Social interaction anxiety positively predicted total and individual depression scores. Greater social interaction anxiety predicted greater self-dislike and worthlessness in men than in women. Our findings replicate the finding that social anxiety and depression are highly comorbid with respect to total scores and extend this finding to individual symptoms. Our findings also demonstrate that the relationship between social interaction anxiety and depressive symptoms can be modulated by gender identities. Men with social interaction anxiety may be more prone to distress associated with self/identity. These findings elucidate the specific ways in which social interaction anxiety relates to the constellation of depression symptoms in men and women and highlights the need for more tailored assessment and intervention for socially anxious men and women to target individual dimensions of symptom presentations.

Deep learning based low-cost high-accuracy diagnostic framework for dementia using comprehensive neuropsychological assessment profiles.

BACKGROUND: The conventional scores of the neuropsychological batteries are not fully optimized for diagnosing dementia despite their variety and abundance of information. To achieve low-cost high-accuracy diagnose performance for dementia using a neuropsychological battery, a novel framework is proposed using the response profiles of 2666 cognitively normal elderly individuals and 435 dementia patients who have participated in the Korean Longitudinal Study on Cognitive Aging and Dementia (KLOSCAD). METHODS: The key idea of the proposed framework is to propose a cost-effective and precise two-stage classification procedure that employed Mini Mental Status Examination (MMSE) as a screening test and the KLOSCAD Neuropsychological Assessment Battery as a diagnostic test using deep learning. In addition, an evaluation procedure of redundant variables is introduced to prevent performance degradation. A missing data imputation method is also presented to increase the robustness by recovering information loss. The proposed deep neural networks (DNNs) architecture for the classification is validated through rigorous evaluation in comparison with various classifiers. RESULTS: The k-nearest-neighbor imputation has been induced according to the proposed framework, and the proposed DNNs for two stage classification show the best accuracy compared to the other classifiers. Also, 49 redundant variables were removed, which improved diagnostic performance and suggested the potential of simplifying the assessment. Using this two-stage framework, we could get 8.06% higher diagnostic accuracy of dementia than MMSE alone and 64.13% less cost than KLOSCAD-N alone. CONCLUSION: The proposed framework could be applied to general dementia early detection programs to improve robustness, preciseness, and cost-effectiveness.

RNA design rules from a massive open laboratory.

Self-assembling RNA molecules present compelling substrates for the rational interrogation and control of living systems. However, imperfect in silico models--even at the secondary structure level--hinder the design of new RNAs that function properly when synthesized. Here, we present a unique and potentially general approach to such empirical problems: the Massive Open Laboratory. The EteRNA project connects 37,000 enthusiasts to RNA design puzzles through an online interface. Uniquely, EteRNA participants not only manipulate simulated molecules but also control a remote experimental pipeline for high-throughput RNA synthesis and structure mapping. We show herein that the EteRNA community leveraged dozens of cycles of continuous wet laboratory feedback to learn strategies for solving in vitro RNA design problems on which automated methods fail. The top strategies--including several previously unrecognized negative design rules--were distilled by machine learning into an algorithm, EteRNABot. Over a rigorous 1-y testing phase, both the EteRNA community and EteRNABot significantly outperformed prior algorithms in a dozen RNA secondary structure design tests, including the creation of dendrimer-like structures and scaffolds for small molecule sensors. These results show that an online community can carry out large-scale experiments, hypothesis generation, and algorithm design to create practical advances in empirical science.

Automated band annotation for RNA structure probing experiments with numerous capillary electrophoresis profiles.

MOTIVATION: Capillary electrophoresis (CE) is a powerful approach for structural analysis of nucleic acids, with recent high-throughput variants enabling three-dimensional RNA modeling and the discovery of new rules for RNA structure design. Among the steps composing CE analysis, the process of finding each band in an electrophoretic trace and mapping it to a position in the nucleic acid sequence has required significant manual inspection and remains the most time-consuming and error-prone step. The few available tools seeking to automate this band annotation have achieved limited accuracy and have not taken advantage of information across dozens of profiles routinely acquired in high-throughput measurements. RESULTS: We present a dynamic-programming-based approach to automate band annotation for high-throughput capillary electrophoresis. The approach is uniquely able to define and optimize a robust target function that takes into account multiple CE profiles (sequencing ladders, different chemical probes, different mutants) collected for the RNA. Over a large benchmark of multi-profile datasets for biological RNAs and designed RNAs from the EteRNA project, the method outperforms prior tools (QuSHAPE and FAST) significantly in terms of accuracy compared with gold-standard manual annotations. The amount of computation required is reasonable at a few seconds per dataset. We also introduce an 'E-score' metric to automatically assess the reliability of the band annotation and show it to be practically useful in flagging uncertainties in band annotation for further inspection. AVAILABILITY AND IMPLEMENTATION: The implementation of the proposed algorithm is included in the HiTRACE software, freely available as an online server and for download at http://hitrace.stanford.edu. CONTACT: sryoon@snu.ac.kr or rhiju@stanford.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Lenvatinib, everolimus, and the combination in patients with metastatic renal cell carcinoma: a randomised, phase 2, open-label, multicentre trial.

BACKGROUND: Currently, metastatic renal cell carcinoma is treated with sequential single agents targeting VEGF or mTOR. Here, we aimed to assess lenvatinib, everolimus, or their combination as second-line treatment in patients with metastatic renal cell carcinoma. METHODS: We did a randomised, phase 2, open-label, multicentre trial at 37 centres in five countries and enrolled patients with advanced or metastatic, clear-cell, renal cell carcinoma. We included patients who had received treatment with a VEGF-targeted therapy and progressed on or within 9 months of stopping that agent. Patients were randomised via an interactive voice response system in a 1:1:1 ratio to either lenvatinib (24 mg/day), everolimus (10 mg/day), or lenvatinib plus everolimus (18 mg/day and 5 mg/day, respectively) administered orally in continuous 28-day cycles until disease progression or unacceptable toxic effects. The randomisation procedure dynamically minimised imbalances between treatment groups for the stratification factors haemoglobin and corrected serum calcium. The primary objective was progression-free survival in the intention-to-treat population. This study is closed to enrolment but patients' treatment and follow-up is ongoing. This study is registered with ClinicalTrials.gov, number NCT01136733. FINDINGS: Between March 16, 2012, and June 19, 2013, 153 patients were randomly allocated to receive either the combination of lenvatinib plus everolimus (n=51), single-agent lenvatinib (n=52), or single-agent everolimus (n=50). Lenvatinib plus everolimus significantly prolonged progression-free survival compared with everolimus alone (median 14·6 months [95% CI 5·9-20·1] vs 5·5 months [3·5-7·1]; hazard ratio [HR] 0·40, 95% CI 0·24-0·68; p=0·0005), but not compared with lenvatinib alone (7·4 months [95% CI 5·6-10·2]; HR 0·66, 95% CI 0·30-1·10; p=0·12). Single-agent lenvatinib significantly prolonged progression-free survival compared with everolimus alone (HR 0·61, 95% CI 0·38-0·98; p=0·048). Grade 3 and 4 events occurred in fewer patients allocated single-agent everolimus (25 [50%]) compared with those assigned lenvatinib alone (41 [79%]) or lenvatinib plus everolimus (36 [71%]). The most common grade 3 or 4 treatment-emergent adverse event in patients allocated lenvatinib plus everolimus was diarrhoea (ten [20%]), in those assigned single-agent lenvatinib it was proteinuria (ten [19%]), and in those assigned single-agent everolimus it was anaemia (six [12%]). Two deaths were deemed related to study drug, one cerebral haemorrhage in the lenvatinib plus everolimus group and one myocardial infarction with single-agent lenvatinib. INTERPRETATION: Lenvatinib plus everolimus and lenvatinib alone resulted in a progression-free survival benefit for patients with metastatic renal cell carcinoma who have progressed after one previous VEGF-targeted therapy. Further study of lenvatinib is warranted in patients with metastatic renal cell carcinoma. FUNDING: Eisai Inc.

HiTRACE-Web: an online tool for robust analysis of high-throughput capillary electrophoresis.

To facilitate the analysis of large-scale high-throughput capillary electrophoresis data, we previously proposed a suite of efficient analysis software named HiTRACE (High Throughput Robust Analysis of Capillary Electrophoresis). HiTRACE has been used extensively for quantitating data from RNA and DNA structure mapping experiments, including mutate-and-map contact inference, chromatin footprinting, the Eterna RNA design project and other high-throughput applications. However, HiTRACE is based on a suite of command-line MATLAB scripts that requires nontrivial efforts to learn, use and extend. Here, we present HiTRACE-Web, an online version of HiTRACE that includes standard features previously available in the command-line version and additional features such as automated band annotation and flexible adjustment of annotations, all via a user-friendly environment. By making use of parallelization, the on-line workflow is also faster than software implementations available to most users on their local computers. Free access: http://hitrace.org.

Standardization of RNA chemical mapping experiments.

Chemical mapping experiments offer powerful information about RNA structure but currently involve ad hoc assumptions in data processing. We show that simple dilutions, referencing standards (GAGUA hairpins), and HiTRACE/MAPseeker analysis allow rigorous overmodification correction, background subtraction, and normalization for electrophoretic data and a ligation bias correction needed for accurate deep sequencing data. Comparisons across six noncoding RNAs stringently test the proposed standardization of dimethyl sulfate (DMS), 2'-OH acylation (SHAPE), and carbodiimide measurements. Identification of new signatures for extrahelical bulges and DMS "hot spot" pockets (including tRNA A58, methylated in vivo) illustrates the utility and necessity of standardization for quantitative RNA mapping.

Sex differences in age-varying trends of depressive symptoms, substance use, and their associations among South Korean adults: A Time-Varying Effect Modeling (TVEM) analysis of a nationwide sample.

BACKGROUND: This study investigated sex differences in the age-varying trends of depressive symptoms, substance use, and their relationships throughout the adult lifespan. Using a nationwide sample from South Korea, this study aimed to confirm existing patterns and identify unique characteristics specific to the South Korean context. METHOD: Time-Varying Effect Modeling (TVEM) was applied to data from 17,484 participants (9987 women and 7497 men) in the Korea National Health and Nutrition Examination Survey. RESULTS: Consistent with global trends, the results revealed a higher prevalence of depressive symptoms among women and a greater prevalence of substance use among men. However, the findings also illuminated unique patterns within the South Korean context. Substance use among South Korean men peaked during their 40s, whereas South Korean women consistently exhibited lower rates of substance use. Additionally, a stronger association between depressive symptoms and substance use was identified in women compared to men. LIMITATIONS: The study used cross-sectional data, limiting the analysis of temporal dynamics between depressive symptoms and substance use. Additionally, TVEM cannot distinguish between aging and cohort effects. Furthermore, the assessments of depressive symptoms and substance use were based on self-report. Finally, the study did not include adolescents or sex and gender minorities in its sample. CONCLUSIONS: These results emphasize the need for targeted interventions, particularly among women in their 20s and older adulthood, where there is a heightened co-occurrence of depressive symptoms and substance use. These findings also highlight the importance of sex- and culture-sensitive approaches tailored to the South Korean context.

Longitudinal dynamics between anxiety and depression in bipolar spectrum disorders.

Anxiety and depression are common among individuals with bipolar spectrum disorders (BSDs), with anxiety being a risk factor for depression and vice versa. While the harmful effects of these symptoms are well recognized, their temporal dynamics have not been fully tested. To address this gap, our study investigated bidirectional relationships between anxiety and depression in individuals with BSDs using data from the Prechter Longitudinal Study of Bipolar Disorder, collected over an average of 11 years. We included 651 participants with various BSD subtypes (BD I, BD II, BD not otherwise specified, and schizoaffective bipolar type), with at least 5 years' data for adequate statistical power in detecting temporal dynamics. Bimonthly measurements of anxiety and depression were analyzed using dynamic structural equation modeling. Beyond assessing autoregressive and cross-lagged effects, this study also investigated whether temporal dynamics differed based on demographic characteristics and the use of psychiatric medication. Our findings revealed that individuals with BSDs experienced significant fluctuations in anxiety and depression over time. In addition, we found significant autoregressive and cross-lagged effects of anxiety and depression. Comparison of the cross-lagged effects demonstrated that anxiety had a greater effect on subsequent depression than vice versa. Age and marital status impacted cross-lagged and autoregressive effects. Specifically, older participants had stronger temporal associations between depression and subsequent anxiety, while widowed participants exhibited a heightened impact of depression on subsequent depression. These results underscore the importance of early identification and integrative interventions aimed at addressing both anxiety and depression to mitigate subsequent symptoms in BSDs. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

An initial test of the contrast avoidance model in bipolar spectrum disorders.

The Contrast Avoidance Model suggests that individuals sensitive to negative emotional shifts use prior increases in negative affect to prevent further escalation in response to adverse situations, while the heightened negative affect amplifies positive emotional contrasts when encountering unexpected positive events. Individuals with bipolar spectrum disorders (BSDs), characterized by shifts between (hypo)manic and depressive episodes, may undergo more salient emotional contrasts. Drawing from the Contrast Avoidance Model, the shifts from depression to (hypo)mania can be conceptualized as positive emotional contrasts, potentially heightening the perceived pleasure during (hypo)manic episodes. On the other hand, the shifts from (hypo)manic to depressive episodes can be viewed as negative emotional contrasts, contributing to the challenges associated with depressive states. Despite the intriguing potential of this interplay, the link between the Contrast Avoidance Model and BSDs has never been empirically tested. Our study addressed this gap by examining group differences in contrast avoidance traits between individuals with BSDs, unipolar depression, and healthy controls in a large cohort study (N = 536). Results indicated that individuals with BSDs exhibited significantly higher scores in the total, and Discomfort with Negative Emotional Shifts and Avoidance of Negative Emotional Contrasts/Enhancement of Positive Emotional Contrasts factors, as well as separate item scores on the Contrast Avoidance Questionnaire-General Emotion (CAQ-GE), compared to those with unipolar depression and healthy controls. Although marginal, the BD II subtype demonstrated a stronger inclination to avoid negative emotional contrasts compared to BD I. These findings suggest that contrast avoidance may be a psychological mechanism implicated in BSDs.

Investigating Electrode-Ionomer Interface Phenomena for Electrochemical Energy Applications.

The endeavor to develop high-performance electrochemical energy applications has underscored the growing importance of comprehending the intricate dynamics within an electrode's structure and their influence on overall performance. This review investigates the complexities of electrode-ionomer interactions, which play a critical role in optimizing electrochemical reactions. Our examination encompasses both microscopic and meso/macro scale functions of ionomers at the electrode-ionomer interface, providing a thorough analysis of how these interactions can either enhance or impede surface reactions. Furthermore, this review explores the broader-scale implications of ionomer distribution within porous electrodes, taking into account factors like ionomer types, electrode ink formulation, and carbon support interactions. We also present and evaluate state-of-the-art techniques for investigating ionomer distribution, including electrochemical methods, imaging, modeling, and analytical techniques. Finally, the performance implications of these phenomena are discussed in the context of energy conversion devices. Through this comprehensive exploration of intricate interactions, this review contributes to the ongoing advancements in the field of energy research, ultimately facilitating the design and development of more efficient and sustainable energy devices.

Structure-Guided Engineering of Thermodynamically Enhanced SaCas9 for Improved Gene Suppression.

Proteins with multiple domains play pivotal roles in various biological processes, necessitating a thorough understanding of their structural stability and functional interplay. Here, a structure-guided protein engineering approach is proposed to develop thermostable Cas9 (CRISPR-associated protein 9) variant for CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) interference applications. By employing thermodynamic analysis, combining distance mapping and molecular dynamics simulations, deletable domains are identified to enhance stability while preserving the DNA recognition function of Cas9. The resulting engineered Cas9, termed small and dead form Cas9, exhibits improved thermostability and maintains target DNA recognition function. Cryo-electron microscopy analysis reveals structural integrity with reduced atomic density in the deleted domain. Fusion with functional elements enables intracellular delivery and nuclear localization, demonstrating efficient gene suppression in diverse cell types. Direct delivery in the mouse brain shows enhanced knockdown efficiency, highlighting the potential of structure-guided engineering to develop functional CRISPR systems tailored for specific applications. This study underscores the significance of integrating computational and experimental approaches for protein engineering, offering insights into designing tailored molecular tools for precise biological interventions.

Worry and rumination enhance a positive emotional contrast based on the framework of the Contrast Avoidance Model.

The Contrast Avoidance Model (CAM) suggests that worry increases negative affect and decreases positive affect. CAM also suggests that in response to a positive event, higher worry enhances the probability of experiencing greater decreased negative affect and increased positive affect (positive emotional contrasts; PECs). Consequently, worrying may be reinforced by repeated PECs. However, no study has tested whether rumination enhances PECs. Also, emotional specificity in these processes has not been considered. Therefore, we tested whether both rumination and worry enhanced PECs related to specific emotions. After resting baseline, participants with pure generalized anxiety disorder (GAD group, n = 91), pure depression symptoms (depression group, n = 91), and non-GAD and non-depressed healthy controls (HCs, n = 93) engaged with randomly assigned induction tasks (either worry, rumination, or relaxation), and then watched an amusement video. Regardless of group, both worry and rumination increased sadness and fear and decreased amusement more than relaxation from baseline. However, worry increased fear more than rumination, and rumination increased sadness more than worry. Although all inductions led to PECs during the video, worry enhanced fear PECs more than rumination, and rumination enhanced sadnessPECs more than worry. The GAD group who worried experienced the most salient PEC of amusement relative to other groups.

A transdiagnostic evaluation of contrast avoidance across generalized anxiety disorder, major depressive disorder, and social anxiety disorder.

BACKGROUND: The contrast avoidance model (CAM) proposes that persons with generalized anxiety disorder (GAD) are sensitive to sharp increases in negative emotion or decreases in positive emotion (i.e., negative emotional contrasts; NEC) and use worry to avoid NEC. Sensitivity to and avoidance of NEC could also be a shared feature of major depressive disorder (MDD) and social anxiety disorder (SAD). METHODS: In a large college sample (N = 1409), we used receiver operating characteristics analysis to examine the accuracy of a measure of emotional contrast avoidance in detecting probable GAD, MDD, and SAD. RESULTS: Participants with probable GAD, MDD, and SAD all reported higher levels of contrast avoidance than participants without the disorder (Cohen's d = 1.32, 1.62 and 1.53, respectively). Area under the curve, a measure of predictive accuracy, was 0.81, 0.87, and 0.83 for predicting probable GAD, MDD, and SAD, respectively. A cutoff score of 48.5 optimized predictive accuracy for probable GAD and SAD, and 50.5 optimized accuracy for probable MDD. CONCLUSION: A measure of emotional contrast avoidance demonstrated excellent ability to predict probable GAD, MDD, and SAD. Sensitivity to and avoidance of NEC appears to be a transdiagnostic feature of these disorders.

Childhood trauma relates to worse memory functioning in bipolar disorder.

BACKGROUND: Childhood trauma is commonly experienced by individuals diagnosed with bipolar disorder (BP). In BP, childhood trauma is related to a more severe clinical course, but its association with cognition remains unclear. METHODS: This study evaluated 405 adult participants diagnosed with BP and 136 controls. Participants completed the Childhood Trauma Questionnaire and a comprehensive neuropsychological battery. High versus low childhood trauma was defined with one standard deviation above the control participant's mean Childhood Trauma Questionnaire score. Neuropsychological data was transformed into eight cognitive factors, including four executive functioning, auditory and visual memory, fine motor, and emotion processing. Multivariate analysis of covariance evaluated group differences in cognition, while adjusting for covariates. RESULTS: There were significant differences among the three groups, F(16, 968) = 4.05, p < .001, Wilks' Λ = 0.88, partial η2 = 0.06. Comparing the high and low trauma BP groups, high trauma was related to lower auditory and visual memory factor scores (p < .05). As compared to controls, the BP high trauma group had lower scores on six of eight factors (all p < .01), while the BP low trauma group had lower scores on four of eight factors (all p < .01). LIMITATIONS: Analyses of factor score do not address which aspect of the memory process is affected and biomarkers may help guide interventions addressing underlying biological process. CONCLUSIONS: Adults diagnosed with BP with higher childhood trauma have worse memory functioning, beyond the lower childhood trauma BP group, highlighting the importance of understanding the long-term cognitive outcomes of childhood trauma.

HiTRACE: high-throughput robust analysis for capillary electrophoresis.

MOTIVATION: Capillary electrophoresis (CE) of nucleic acids is a workhorse technology underlying high-throughput genome analysis and large-scale chemical mapping for nucleic acid structural inference. Despite the wide availability of CE-based instruments, there remain challenges in leveraging their full power for quantitative analysis of RNA and DNA structure, thermodynamics and kinetics. In particular, the slow rate and poor automation of available analysis tools have bottlenecked a new generation of studies involving hundreds of CE profiles per experiment. RESULTS: We propose a computational method called high-throughput robust analysis for capillary electrophoresis (HiTRACE) to automate the key tasks in large-scale nucleic acid CE analysis, including the profile alignment that has heretofore been a rate-limiting step in the highest throughput experiments. We illustrate the application of HiTRACE on 13 datasets representing 4 different RNAs, 3 chemical modification strategies and up to 480 single mutant variants; the largest datasets each include 87 360 bands. By applying a series of robust dynamic programming algorithms, HiTRACE outperforms prior tools in terms of alignment and fitting quality, as assessed by measures including the correlation between quantified band intensities between replicate datasets. Furthermore, while the smallest of these datasets required 7-10 h of manual intervention using prior approaches, HiTRACE quantitation of even the largest datasets herein was achieved in 3-12 min. The HiTRACE method, therefore, resolves a critical barrier to the efficient and accurate analysis of nucleic acid structure in experiments involving tens of thousands of electrophoretic bands.

vHoT: a database for predicting interspecies interactions between viral microRNA and host genomes.

Some viruses have been reported to transcribe microRNAs, implying complex relationships between the host and the pathogen at the post-transcriptional level through microRNAs in virus-infected cells. Although many computational algorithms have been developed for microRNA target prediction, few have been designed exclusively to find cellular or viral mRNA targets of viral microRNAs in a user-friendly manner. To address this, we introduce the viral microRNA host target (vHoT) database for predicting interspecies interactions between viral microRNA and host genomes. vHoT supports target prediction of 271 viral microRNAs from human, mouse, rat, rhesus monkey, cow, and virus genomes. vHoT is freely available at http://dna.korea.ac.kr/vhot.

Avoidance of negative emotional contrast from worry and rumination: An application of the Contrast Avoidance Model.

According to the Contrast Avoidance model (CAM), worry causes increased and sustained negative affect and such negative affect enables avoidance of a future sharp increase in negative emotion. However, only pathological worriers (vs. controls) view worry as a positive coping strategy to avoid a negative emotional contrast (NEC). We examined if rumination, which is another type of repetitive negative thought, would function similarly. Individuals with self-reported symptoms of pure generalized anxiety disorder (GAD; n = 90), pure depression (MDD; n = 85), and non-anxious/non-depressed controls (HC; n = 93) were randomly assigned to conditions where they were asked to worry, ruminate, or relax. Emotional and physiological changes were measured during worry and subsequent exposure to fearful and sad videos. We also assessed participant group differences in preference for worry or rumination as a strategy to cope with negative affect during the negative emotional video exposures. Consistent with CAM, regardless of the group, both worry and rumination enabled avoidance of NEC. Whereas worry led to greater avoidance of a fear contrast, rumination led to greater avoidance of a sadness contrast. On the other hand, relaxation enhanced NEC. Skin conductance also indicated patterns in line with CAM. In the subjectively perceived preference, the GAD group reported a greater preference for worry in coping with a fear contrast than HC. However, such a salient pattern was not found for the MDD group. Treatment implications of these findings are discussed.

The naturalistic reinforcement of worry from positive and negative emotional contrasts: Results from a momentary assessment study within social interactions.

BACKGROUND: The Contrast Avoidance Model (Newman & Llera, 2011) proposes that worry is reinforced by avoiding a negative contrast and increasing the likelihood of a positive contrast. OBJECTIVE: To determine if reinforcement of worry occurs naturalistically via contrasts in both negative and positive emotion. METHOD: Using event-contingent momentary assessment we assessed social interactions, pre-interaction state worry and pre-post interaction positive and negative emotion. Participants with generalized anxiety disorder (GAD; N = 83) completed an online questionnaire after social interactions lasting at least 1 min for 8 days. Three-level multilevel models were conducted. RESULTS: Higher worry was concurrently associated with increased negative emotion and decreased positive emotion. Regardless of pre-interaction worry level, negative emotion decreased, and positive emotion increased from before to after interactions, suggesting that most interactions were benign or positive. At lower levels of pre-interaction worry, participants experienced increased negative emotion and decreased positive emotion from before to after interactions. At higher levels of pre-interaction worry, participants experienced decreased negative emotion and increased positive emotion from before to after interactions. CONCLUSION: Among persons with GAD, worrying before social interactions may be both negatively and positively reinforced; furthermore, not worrying before social interactions may be both negatively and positively punished.

College Mental Health Before and During the COVID-19 Pandemic: Results From a Nationwide Survey.

Background: The COVID-19 pandemic could affect college students' mental health. We examined screening rates for psychological disorders before and during the pandemic. Methods: Undergraduates were surveyed before (n = 3643) or during the pandemic (n = 4970). Logistic regression adjusting for participant demographics was conducted. Results: Frequencies of depression [OR 1.32, 95% CI (1.17, 1.48)], alcohol use disorder [OR 1.70, 95% CI (1.50, 1.93)], bulimia nervosa/binge-eating disorder [OR 1.54, 95% CI (1.28, 1.85)], and comorbidity [OR 1.19, 95% CI (1.04, 1.35)] were greater during (vs. before) the pandemic. Frequencies of posttraumatic stress disorder were lower during the pandemic [OR 0.86, 95% CI (0.75, 0.98)]. The upward trend in alcohol use disorder was stronger among women than men [OR 1.47, 95% CI (1.18, 1.83)]. The upward trend in depression was stronger among Black students than White students [OR 1.72, 95% CI (1.19, 2.49)]. Anxiety disorders, insomnia, anorexia nervosa, and suicidality showed no significant trends. Conclusions: Depression, alcohol use disorder, bulimia nervosa/binge-eating disorder, and comorbidity were higher, whereas posttraumatic stress disorder was lower during the pandemic. Women and Black students could face especially heightened risk for alcohol use disorder and depression, respectively, during the pandemic.