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Community participation is associated with physical, cognitive, and mental health benefits for people with serious mental illnesses (SMI) and is recognized as a critical component of health functioning. Developing reliable measurement of participation in different cultural contexts and languages is important to expanding knowledge in this area. The aim of this study was to translate a psychometrically sound English-language community participation measure into Japanese and examine its test-reliability with a population of Japanese people with SMI. Self-reported data were gathered twice from 253 individuals within 48 h using the Temple University Community Participation-Japanese version (TUCP-J) at Type-B Continuous Employment Support Centers in Japan between November 2020 and February 2021. Participant responses were similar on four of the five participation subscales. At the item-level, participants provided consistent responses on 26 out of 27 of the items about amount of participation and had high item-level concordance (77-93%) on their ratings of the importance (Yes; No) of each participation activity and their reported participation sufficiency (Enough; Not Enough; Too Much 73-88%). Overall, the results demonstrated strong evidence of test-retest reliability of the TUCP-J and identified a number of areas that were important to respondents, but where they were reporting not doing enough.[This corrects the article DOI 10.1055/a-1629-7540.].

Due to the COVID-19 pandemic, many universities moved to emergency remote teaching (ERT). This allowed institutions to continue their instruction despite not being in person. However, ERT is not without consequences. For example, students may have inadequate technological supports, such as reliable internet and computers. Students may also have poor learning environments at home and may need to find added employment to support their families. In addition, there are consequences to faculty. It has been shown that female instructors are more disproportionately impacted in terms of mental health issues and increased domestic labor. This research aims to investigate instructors’ and students’ perceptions of their transition to ERT. Specifically, during the transition to ERT at a research-intensive, Minority-Serving Institution (MSI), we wanted to (1) Identify supports and barriers experienced by instructors and students. (2) Compare instructors’ experiences with the students’ experiences. (3) Explore these suppularly at MSIs, where improved communication and increased access to resources for both students and instructors are key.

The online version contains supplementary material available at 10.1186/s40594-022-00335-1.

The online version contains supplementary material available at 10.1186/s40594-022-00335-1.

In the context of an ongoing, highly uncertain pandemic, disaster mental health measures can increase community capacity for resilience and well-being, support formal mental health treatment, and help address the risk for mental health reactions in high-stress occupations. The purpose of this review is to summarize the literature on disaster mental health interventions that have been helpful both prior to and during the pandemic in a broad range of applications, including for use with high-stress occupations in an effort to mitigate risk for post-traumatic stress disorder (PTSD) and other mental health sequelae.

Evidence-based and evidence-informed disaster mental health interventions, frameworks, and treatments have been studied in pilot studies, non-randomized trials, and randomized clinical trials prior to and in the context of the current COVID-19 pandemic. The studies have demonstrated feasibility and acceptability of these modalities and improved perceived support, as well as significant reductions in distress, and mental health symptoms such as depression, anxiety, and PTSD.

A disaster mental health approach to the COVID-19 pandemic can generate opportunities for prevention and support at multiple levels with timely interventions tailored for different concerns, cultures, and available resources.

A disaster mental health approach to the COVID-19 pandemic can generate opportunities for prevention and support at multiple levels with timely interventions tailored for different concerns, cultures, and available resources.

This review highlights six “best practices” for cancer epidemiology coordinating centers to facilitate the success of a research consortium.

Evidence from emerging literature regarding the Science of Team Science suggests that coordinating centers can more effectively foster collaborative cancer epidemiology research in consortia by (1) establishing collaboration as a shared goal at the start, (2) providing scientific expertise complementary to the research sites that adapts over the course of the project, (3) enacting anti-racist and inclusive approaches in all consortium decisions and activities, (4) fostering early-stage investigator career development, (5) engaging stakeholders including cancer survivors as peers, and (6) delivering reliable logistical support and technology tools with planned process evaluation so that researchers can collaboratively focus on the science.

By drawing on the Science of Team Science, coordinating centers can accelerate research progress and increase the impact of cancer epidemiology consortia.

By drawing on the Science of Team Science, coordinating centers can accelerate research progress and increase the impact of cancer epidemiology consortia.

Suicide is the second leading cause of death among Black youth ages 10-19 years. Between 1991 and 2017, rates of suicide among Black youth have been increasing faster than rates among any other race/ethnic group. There are many factors that may explain this increase, with gambling being suggested as one such potential risk factor. This review examines the association between gambling and suicide behaviors, and how these associations may vary between Black and White youth and young adults. The current review examines these associations using data from the Missouri Family Study (MOFAM).

Recent findings have revealed distinct patterns of substance use initiation and gambling behaviors between Black youth and White youth. While strong links between gambling and suicide behaviors have also been reported, whether the associations were consistent across race/ethnicity groups was not investigated, nor in these cross-sectional analyses was it possible to determine whether the gambling behaviors preceded or followeack youth.

The current findings revealed that gambling initiation predicted suicide ideation among Black youth, while no significant association was found among White youth. This is of major public health concern, given the rising rates of suicide among Black youth, and the increased availability of gambling. The report did not find a link between gambling and suicide attempts. Culturally tailored interventions should be considered among schools, families, and clinicians/providers, to highlight the risk of adolescent gambling, particularly among Black youth.

The abuse of opioids induces many terrible problems in human health and social stability. For opioid-dependent individuals, withdrawal memory can be reactivated by context, which is then associated with extremely unpleasant physical and emotional feelings during opioid withdrawal. The reactivation of withdrawal memory is considered one of the most important reasons for opioid relapse, and it also allows for memory modulation based on the reconsolidation phenomenon. However, studies exploring withdrawal memory modulation during the reconsolidation window are lacking. By summarizing the previous findings about the reactivation of negative emotional memories, we are going to suggest potential neural regions and systems for modulating opioid withdrawal memory.

Here, we first present the role of memory reactivation in its modification, discuss how the hippocampus participates in memory reactivation, and discuss the importance of noradrenergic signaling in the hippocampus for memory reactivation. Then, we review the engagement of other limbic regions receiving noradrenergic signaling in memory reactivation. We suggest that noradrenergic signaling targeting hippocampus neurons might play a potential role in strengthening the disruptive effect of withdrawal memory extinction by facilitating the degree of memory reactivation.

This review will contribute to a better understanding of the mechanisms underlying reactivation-dependent memory malleability and will provide new therapeutic avenues for treating opioid use disorders.

This review will contribute to a better understanding of the mechanisms underlying reactivation-dependent memory malleability and will provide new therapeutic avenues for treating opioid use disorders.Online social networks have attracted billions of active users over the past decade. These systems play an integral role in the everyday life of many people around the world. As such, these platforms are also attractive for misinformation, hoaxes, and fake news campaigns which usually utilize social trolls and/or social bots for propagation. Detection of so-called social trolls in these platforms is challenging due to their large scale and dynamic nature where users’ data are generated and collected at the scale of multi-billion records per hour. In this paper, we focus on fickle trolls, i.e., a special type of trolling activity in which the trolls change their identity frequently to maximize their social relations. This kind of trolling activity may become irritating for the users and also may pose a serious threat to their privacy. selleck inhibitor To the best of our knowledge, this is the first work that introduces mechanisms to detect these trolls. In particular, we discuss and analyze troll detection mechanisms on different scales. We prove that the order of centralized single-machine detection algorithm is O ( n 3 ) which is slow and impractical for early troll detection in large-scale social platforms comprising of billions of users. We also prove that the streaming approach where data is gradually fed to the system is not practical in many real-world scenarios. In light of such shortcomings, we then propose a massively parallel detection approach. Rigorous evaluations confirm that our proposed method is at least six times faster compared to conventional parallel approaches.Social media has great importance in the community for discussing many events and sharing them with others. The primary goal of this research is to study the quality of the sentiment analysis (SA) of impressions about Saudi cruises, as a first event, by creating datasets from three selected social media platforms (Instagram, Snapchat, and Twitter). The outcome of this study will help in understanding opinions of passengers and viewers about their first Saudi cruise experiences by analyzing their feelings from social media posts. After cleaning, this experiment contains 1200 samples. The data was classified into positive or negative classes using the choice of machine learning algorithms, such as multilayer perceptron (MLP), naıve bayes (NB), random forest (RF), support vector machine (SVM), and voting. The results show the highest classification accuracy for the RF algorithm, as it achieved 100% accuracy with over-sampled data from Snapchat using both test options. The algorithms were compared among the three different datasets.