Efficacy of REACH Forgiveness across Cultures

Across cultures, most people agree that forgiveness is a virtue. However, culture may influence how willing one should be to forgive and how one might express forgiveness. At a university in the United States, we recruited both foreign-extraction students and domestic students (N = 102) to participate in a six-hour REACH Forgiveness intervention. We investigated the efficacy of the intervention overall as well as whether foreign-extraction and domestic students responded differently to treatment. Forgiveness was assessed using two measures—decisional forgiveness and emotional forgiveness. The six-hour REACH Forgiveness intervention improved participants’ ratings of emotional forgiveness, but not decisional forgiveness, regardless of their culture. Thus, the REACH Forgiveness intervention appears equally efficacious for participants from different cultural backgrounds when conducted in the United States with college students

Gestational Exposure to Antidepressants and Risk of Seizure in Offspring: A systematic review and meta-analysis

In spite of the preliminary evidence suggesting a link between gestational use of antidepressant and neurodevelopmental disorders in their offspring, the association between maternal use of antidepressants during pregnancy and the risk of neurologically-related adverse outcomes such as neonatal seizure is still unclear. This study summarises the available evidence on the association between gestational exposure to any antidepressants and the risk of seizure in neonates and children. We found that gestational antidepressant exposure is associated with a 2.3-fold higher incidence of seizure in offspring. Although a causal relationship cannot be confirmed in view of other potential confounders, our findings warrant future research on related clinical aspects, and possibly more careful monitoring of foetal neurodevelopment in pregnant women taking antidepressants during pregnancy. However, this does not suggest the abrupt withdrawal of antidepressants during pregnancy for all cases at risk of seizure in offspring as this must be balanced with the risk of negative consequences caused by untreated maternal depression, and decision-making should be individualised for each patient

Multiplpe Choice Minority Game With Different Publicly Known Histories

In the standard Minority Game, players use historical minority choices as the sole public information to pick one out of the two alternatives. However, publishing historical minority choices is not the only way to present global system information to players when more than two alternatives are available. Thus, it is instructive to study the dynamics and cooperative behaviors of this extended game as a function of the global information provided. We numerically find that although the system dynamics depends on the kind of public information given to the players, the degree of cooperation follows the same trend as that of the standard Minority Game. We also explain most of our findings by the crowd-anticrowd theory.Comment: Extensively revised, to appear in New J Phys, 7 pages with 4 figure

A component-based macro-mechanical model for inter-module connections in steel volumetric buildings

Inter-module connections (IMC) are a research focus closely related to the robustness of steel volumetric buildings (VB). Many IMC have been proposed by numerous researchers and engineers, experimentally tested and numerically studied using finite element models. However, there are insufficient IMC macro models available, which imposes challenges for engineers to construct a global numerical VB model. Hence, this study aims to close the gap with a component-based macro-mechanical model for the macro-modelling of IMC in steel VB. In this paper, a comprehensive IMC database was collected to identify and characterise the active components. Two types of macro-mechanical models (H-shape and Q-shape) consisting of P-V-M links have been proposed and a novel uplifting mechanism has been derived for a typical IMC (bolted tie plate with shear key). The proposed macro-mechanical model and other existing macro-models were then compared with existing pushover experiments from an IMC subassembly. The proposed macro-mechanical model shows a good match to the existing experimental results, and it is adaptable to existing IMC.</p

Spacetime Emergence and General Covariance Transmutation

Spacetime emergence refers to the notion that classical spacetime "emerges" as an approximate macroscopic entity from a non-spatio-temporal structure present in a more complete theory of interacting fundamental constituents. In this article, we propose a novel mechanism involving the "soldering" of internal and external spaces for the emergence of spacetime and the twin transmutation of general covariance. In the context of string theory, this mechanism points to a critical four dimensional spacetime background.Comment: 11 pages, v2: version to appear in MPL

Forgiveness of In-group Offenders in Christian Congregations

Religious communities, like other communities, are ripe for interpersonal offenses. We examined the degree to which group identification predicted forgiveness of an in-group offender. We examined the effects of a victim’s perception of his or her religious group identification as a state-specific personal variable on forgiveness by integrating Social Identity Theory into a model of Relational Spirituality (Davis, Hook, & Worthington, 2008) to help explain victim’s responses to transgressions within a religious context. Data were collected from members of Christian congregations from the mid-west region of the United States (Study 1, N = 63), and college students belonging to Christian congregations (Study 2, N = 376). Regression analyses demonstrated that even after statistically controlling for many religious and transgression-related variables, group identification with a congregation still predicted variance in revenge and benevolence toward an in-group offender after a transgression. Additionally, mediation analyses suggest group identification as one mechanism through which trait forgivingness relates to forgiveness of specific offenses. We discuss the importance of group identity in forgiving other in-group members in a religious community

Qigong Exercise Alleviates Fatigue, Anxiety, and Depressive Symptoms, Improves Sleep Quality, and Shortens Sleep Latency in Persons with Chronic Fatigue Syndrome-Like Illness

Objectives:. To evaluate the effectiveness of Baduanjin Qigong exercise on sleep, fatigue, anxiety, and depressive symptoms in chronic fatigue syndrome- (CFS-) like illness and to determine the dose-response relationship. Methods:. One hundred fifty participants with CFS-like illness (mean age = 39.0, SD = 7.9) were randomly assigned to Qigong and waitlist. Sixteen 1.5-hour Qigong lessons were arranged over 9 consecutive weeks. Pittsburgh Sleep Quality Index (PSQI), Chalder Fatigue Scale (ChFS), and Hospital Anxiety and Depression Scale (HADS) were assessed at baseline, immediate posttreatment, and 3-month posttreatment. The amount of Qigong self-practice was assessed by self-report. Results:. Repeated measures analyses of covariance showed a marginally nonsignificant (P = 0.064) group by time interaction in the PSQI total score, but it was significant for the “subjective sleep quality” and “sleep latency” items, favoring Qigong exercise. Improvement in “subjective sleep quality” was maintained at 3-month posttreatment. Significant group by time interaction was also detected for the ChFS and HADS anxiety and depression scores. The number of Qigong lessons attended and the amount of Qigong self-practice were significantly associated with sleep, fatigue, anxiety, and depressive symptom improvement. Conclusion:. Baduanjin Qigong was an efficacious and acceptable treatment for sleep disturbance in CFS-like illness. This trial is registered with Hong Kong Clinical Trial Register: HKCTR-1380

Major adverse cardiovascular events of enzalutamide versus abiraterone in prostate cancer: a retrospective cohort study.

Background While the cardiovascular risks of androgen receptor pathway inhibitors have been studied, they were seldom compared directly. This study compares the risks of major adverse cardiovascular events (MACE) between enzalutamide and abiraterone among prostate cancer (PCa) patients. Methods Adult PCa patients receiving either enzalutamide or abiraterone in addition to androgen deprivation therapy in Hong Kong between 1 December 1999 and 31 March 2021 were identified in this retrospective cohort study. Patients who switched between enzalutamide and abiraterone, initiated abiraterone used without steroids, or experienced prior cardiac events were excluded. Patients were followed-up until 30 September 2021. The primary outcomes were MACE, a composite of stroke, myocardial infarction (MI), Heart failure (HF), or all-cause mortality and a composite of adverse cardiovascular events (CACE) not including all-cause mortality. The secondary outcomes were individual components of MACE. Inverse probability treatment weighting was used to balance covariates between treatment groups. Results In total, 1015 patients were analyzed (456 enzalutamide users and 559 abiraterone users; mean age 70.6 ± 8.8 years old) over a median follow-up duration of 11.3 (IQR: 5.3–21.3) months. Enzalutamide users had significantly lower risks of 4P-MACE (weighted hazard ratio (wHR) 0.71 [95% confidence interval (CI) 0.59–0.86], p < 0.001) and CACE (wHR 0.63 [95% CI: 0.42–0.96], p = 0.031), which remained consistent in multivariable analysis. Such an association may be stronger in patients aged ≥65 years or without diabetes mellitus and was independent of bilateral orchidectomy. Enzalutamide users also had significantly lower risks of MI (wHR 0.57 [95% CI: 0.33–0.97], p = 0.040) and all-cause mortality (wHR 0.71 [95% CI: 0.59–0.85], p < 0.001). Conclusion Enzalutamide was associated with lower cardiovascular risks than abiraterone in PCa patients

Bipolar disorder with binge eating behavior: a genome-wide association study implicates PRR5-ARHGAP8

Bipolar disorder (BD) is associated with binge eating behavior (BE), and both conditions are heritable. Previously, using data from the Genetic Association Information Network (GAIN) study of BD, we performed genome-wide association (GWA) analyses of BD with BE comorbidity. Here, utilizing data from the Mayo Clinic BD Biobank (969 BD cases, 777 controls), we performed a GWA analysis of a BD subtype defined by BE, and case-only analysis comparing BD subjects with and without BE. We then performed a meta-analysis of the Mayo and GAIN results. The meta-analysis provided genome-wide significant evidence of association between single nucleotide polymorphisms (SNPs) in PRR5-ARHGAP8 and BE in BD cases (rs726170 OR=1.91, P=3.05E-08). In the meta-analysis comparing cases with BD with comorbid BE vs. non-BD controls, a genome-wide significant association was observed at SNP rs111940429 in an intergenic region near PPP1R2P5 (p=1.21E-08). PRR5-ARHGAP8 is a read-through transcript resulting in a fusion protein of PRR5 and ARHGAP8. PRR5 encodes a subunit of mTORC2, a serine/threonine kinase that participates in food intake regulation, while ARHGAP8 encodes a member of the RhoGAP family of proteins that mediate cross-talk between Rho GTPases and other signaling pathways. Without BE information in controls, it is not possible to determine whether the observed association reflects a risk factor for BE in general, risk for BE in individuals with BD, or risk of a subtype of BD with BE. The effect of PRR5-ARHGAP8 on BE risk thus warrants further investigation

Predicting Opioid Use Outcomes in Minoritized Communities

Machine learning algorithms can sometimes exacerbate health disparities based on ethnicity, gender, and other factors. There has been limited work at exploring potential biases within algorithms deployed on a small scale, and/or within minoritized communities. Understanding the nature of potential biases may improve the prediction of various health outcomes. As a case study, we used data from a sample of 539 young adults from minoritized communities who engaged in nonmedical use of prescription opioids and/or heroin. We addressed the indicated issues through the following contributions: 1) Using machine learning techniques, we predicted a range of opioid use outcomes for participants in our dataset; 2) We assessed if algorithms trained only on a majority sub-sample (e.g., Non-Hispanic/Latino, male), could accurately predict opioid use outcomes for a minoritized sub-sample (e.g., Latino, female). Results indicated that models trained on a random sample of our data could predict a range of opioid use outcomes with high precision. However, we noted a decrease in precision when we trained our models on data from a majority sub-sample, and tested these models on a minoritized sub-sample. We posit that a range of cultural factors and systemic forms of discrimination are not captured by data from majority sub-samples. Broadly, for predictions to be valid, models should be trained on data that includes adequate representation of the groups of people about whom predictions will be made. Stakeholders may utilize our findings to mitigate biases in models for predicting opioid use outcomes within minoritized communities