COVID-19 Stress and Sexual Identities

The COVID-19 pandemic has disrupted lives and resulted in high levels of stress. While the evidence at the societal level is clear, there have been no population-based studies of pandemic-based stress focusing on individuals who identify as sexual minorities. Drawing on representative data collected during the pandemic, National Couples’ Health and Time Use Study, we find that partnered (cohabiting or married) individuals who identified as sexual minorities experienced higher levels of stress than individuals who identified as heterosexual. However, variation exists observed among sexual minority adults. Although economic resources, discrimination, social and community support and health conditions are tied to reported stress levels they do not explain differentials according to sexual identity. These results provide evidence that sexual minority adults faced greater stress during the pandemic and the importance of recognizing that sexual minorities are not a monolithic group with varying stress responses to the pandemic.

Cluster Forecasting of Corruption Using Nonlinear Autoregressive Models with Exogenous Variables (NARX)—An Artificial Neural Network Analysis

Any effort to combat corruption can benefit from an examination of past and projected worldwide trends. In this paper, we forecast the level of corruption in countries by integrating artificial neural network modeling and time series analysis. The data were obtained from 113 countries from 2007 to 2017. The study is carried out at two levels: (a) the global level, where all countries are considered as a monolithic group; and (b) the cluster level, where countries are placed into groups based on their development-related attributes. For each cluster, we use the findings from our previous study on the cluster analysis of global corruption using machine learning methods that identified the four most influential corruption factors, and we use those as independent variables. Then, using the identified influential factors, we forecast the level of corruption in each cluster using nonlinear autoregressive recurrent neural network models with exogenous inputs (NARX), an artificial neural network technique. The NARX models were developed for each cluster, with an objective function in terms of the Corruption Perceptions Index (CPI). For each model, the optimal neural network is determined by fine-tuning the hyperparameters. The analysis was repeated for all countries as a single group. The accuracy of the models is assessed by comparing the mean square errors (MSEs) of the time series models. The results suggest that the NARX artificial neural network technique yields reliable future values of CPI globally or for each cluster of countries. This can assist policymakers and organizations in assessing the expected efficacies of their current or future corruption control policies from a global perspective as well as for groups of countries.

Factors associated with seasonal influenza and HPV vaccination uptake among different ethnic groups in Arab and Jewish society in Israel

Background Parents in the Arab population of Israel are known to be “pro-vaccination” and vaccinate their children at higher rates than the Jewish population, specifically against human papilloma virus (HPV) and seasonal influenza. Objectives This study seeks to identify and compare variables associated with mothers’ uptake of two vaccinations, influenza and HPV, among different subgroups in Arab and Jewish society in Israel. Methods A cross-sectional study of the entire spectrum of the Israeli population was conducted using a stratified sample of Jewish mothers (n = 159) and Arab mothers (n = 534) from different subgroups: Muslim, Christian, Druse and Northern Bedouins. From March 30, 2019 through October 20, 2019, questionnaires were distributed manually to eighth grade pupils (13–14 years old) who had younger siblings in second (7–8 years old) or third (8–9 years old) grades. Results Arab mothers exhibited a higher rate of uptake for both vaccinations (p < .0001, HPV – 90%; influenza – 62%) than Jewish mothers (p = 0.0014, HPV – 46%; influenza – 34%). Furthermore, results showed that HPV vaccination uptake is significantly higher than seasonal influenza vaccination uptake in both populations. Examination of the different ethnic subgroups revealed differences in vaccination uptake. For both vaccinations, the Northern Bedouins exhibited the highest uptake rate of all the Arab subgroups (74%), followed by the Druse (74%) and Muslim groups (60%). The Christian Arab group exhibited the lowest uptake rate (46%). Moreover, the uptake rate among secular Jewish mothers was lower than in any of the Arab groups (38%), though higher than among religious/traditional Jewish mothers, who exhibited the lowest uptake rate (26%). A comparison of the variables associated with mothers’ vaccination uptake revealed differences between the ethnic subgroups. Moreover, the findings of the multiple logistic regression revealed the following to be the most significant factors in Arab mothers’ intake of both vaccinations: school-located vaccination and mothers’ perceived risk and perceived trust in the system and in the family physician. These variables are manifested differently in the different ethnic groups. Conclusions This research shows that all Arabs cannot be lumped together as one monolithic group in that they exhibit major differences according to religion, education and access to information. Ranking of variables associated with uptake of the two vaccines can provide decision-makers an empirical basis for tailoring appropriate and specific interventions to each subgroup to achieve the highest vaccine uptake rate possible. Media campaigns targeting the Arab population should be segmented to appeal to the various sub-groups according to their viewpoints, needs and health literacy.

Cluster Forecasting of Corruption Using Nonlinear Autoregressive with Exogenous Variables (NARX) – An Artificial Neural Network Analysis

Any effort to combat corruption can benefit from an examination of past and projected worldwide trends. In this paper, we forecast the level of corruption in countries by integrating an artificial neural network modeling and time series analysis. The data were obtained from 113 countries from 2007 to 2017. The study is carried out at two levels: (a) global level where all countries are considered as a monolithic group; and (b) cluster level, where countries are placed into groups based on their development-related attributes. For each cluster, we use the findings from our previous study on the cluster analysis of global corruption using machine learning methods that identified the four most influential corruption factors, and we use those as independent variables. Then, using the identified influential factors, we forecast the level of corruption in each cluster using a nonlinear autoregressive recurrent neural network with exogenous inputs (NARX), an artificial neural network technique. The NARX models were developed for each cluster, with the objective function in terms of the Corruption Perceptions Index (CPI). For each model, the optimal neural network is determined by finetuning the hyperparameters. The analysis was repeated for all countries as a single group. The accuracy of the models is assessed by comparing the mean square errors (MSE) of the time series models. The results suggest that the NARX artificial neural network technique yields reliable future values of CPI globally or for each cluster of countries. This can assist policymakers and organizations in assessing the expected efficacies of their current or future corruption control policies from a global perspective as well as for groups of countries.

Living in Between: A Grounded Theory Study of Depression Among Middle-Class Black Women

Empirical evidence consistently has linked the identification and treatment of depression among low-income Black women. Research on depression and Black women also suggests Black women are a monolithic group who experience depression similarly. The purpose of this qualitative study was to gain a deeper understanding of how the identity of middle-class Black women may shape their experiences with depression. Using grounded theory as the guiding method, I conducted 30 in-depth, semistructured interviews with Black women between 30 and 45 years old who self-identified as middle class. The core experience of depression among middle-class Black women was “living in between” because they straddled two worlds—one Black world and one White world—with competing sociocultural messages about depression. Two major categories emerged that informed the experiences of depression among the middle-class Black women in this study: (a) strategies to deal with depression and (b) minimizing depression. Each of these categories highlighted consequences for the women’s mental health. The women also described coping strategies for managing these experiences. Implications for research and practice are included.

Liberal Activists: Playing by the System and Making Gains

This chapter analyzes the relationships Muslim ‘liberal’ activists have with the state. Just like the ulama, the liberals are not a monolithic group, with various approaches taken by different actors. However, by and large, the liberals, again like the ulama, play by the rules of the game set by the state. In fact, I argue that liberals have managed to maximize their space the most as compared to conservatives, for reasons which are explained in the chapter.

Adolescent Literacies

Naming is a curious practice. It entails rudiments, now mostly taken for granted, that serve to categorize everyday literacy practices across fields as diverse as cultural anthropology and the management of multiple Git profiles. As a term unto itself, adolescent literacies is not immune to the vagaries of naming. In fact, it serves as an excellent example of how commonly named concepts in education embed the field’s histories, debates, pedagogies, and policies writ large. Conceptualizing literacy in its plural form raised eyebrows among academics, researchers, practitioners, publishers, and indexers concerned with the noun–verb agreement in phrases such as “adolescent literacies is a subfield” of adolescence. For some, the very notion of literacy extending beyond reading and writing is still debatable. With each passing day, however, it becomes noticeably more evident that multimodal forms of communication—images, sounds, bodily performances, to name but a few ways of expressing oneself—are competing quite well in the marketplace of ideas that flow globally with or without a linguistic component attached to them. Aside from the naming process and its attendant political overtones, the practice of treating youth between roughly the ages of 12 and 17 as a monolithic group has been common in the United States. Largely traceable to a time in which developmental psychology dominated the field of literacy instruction (in the early to late 20th century), designating youth as adolescents equated to viewing them as some a normative group devoid of racial, class, gender, and any number of other identity markers. Even with the sociocultural turn in early 21st century and its abundance of studies reifying the socially constructed nature of adolescents, the term persists. Its adhesive-like attraction to literacies, however, may be weakening in light of research that points to youth who are agentic and dynamic game changers when it comes to participating in a world grown more attuned to the need for collaboration based not on hierarchical standing but instead on working through commonplace tensions too complex for any one solution.

Islam, Travel, and Learning

This article focuses on the study of the relationship between Islam, travel, and learning by conducting a case study on Indonesian Muslim students who studied (or are studying) in Saudi Arabia. Specifically, it examines the changing dynamics of these students who traveled, immigrated to, and studied in Saudi Arabia in search of knowledge from previous centuries to the contemporary era. This article shows that Indonesian students in this peninsula are deeply plural and complex, far from being a monolithic group in terms of social background, religious affiliation, political orientation, major field of study, and motive of their study, among other factors. Thus, the present article aims at demystifying and challenging the common beliefs and narratives which hold that Saudi Arabia–trained Indonesian students have been exporters of Islamist intolerance, radicalism, or even terrorism.

Comparison of CAD/CAM manufactured implant-supported crowns with different analyses

Background Present study compared the failure load of CAD/CAM-manufactured implant-supported crowns and the stress distribution on the prosthesis-implant-bone complex with different restoration techniques. Methods The materials were divided into four groups: group L-M: lithium disilicate ceramic (LDS, monolithic), group L-V: LDS ceramic (veneering), group ZL-M: zirconia-reinforced lithium silicate ceramic (ZLS, monolithic), group ZL-V: ZLS ceramic (veneering). Crown restorations were subjected to load-to-failure test (0.5 mm/min). Failure loads of each group were statistically analyzed (two-way ANOVA, post hoc Tukey HSD, α = 0.05). Finite element analysis (FEA) was used to compare the stress distribution of crown restorations. Results Group L-M had the highest failure load (2891.88 ± 410.12 N) with a significant difference from other groups (p < 0.05). Although there was a significant difference between group ZL-M (1750.28 ± 314.96 N) and ZL-V (2202.55 ± 503.14 N), there was no significant difference from group L-V in both groups (2077.37 ± 356.59 N) (p > 0.05). Conclusions The veneer application had opposite effects on ceramics, increased the failure load of ZLS and reduced it for LDS without a statistically significant difference. Both materials are suitable for implant-supported crowns. Different restorative materials did not influence the stress distribution, but monolithic restorations reduced the stress concentration on the implant and bone.

An Investigation of Definitions of Experimental Vaping among Youth

Objectives: Identifying which youth are experimenting with vaping could aid the development and evaluation of targeted media campaigns and research and surveillance activities. In this study, we sought to identify behavioral definitions that best differentiate youth experimenters and established vapers. Methods: We conducted an online survey with a non-probability sample of 1500 youth aged 13-17 who reported ever vaping. Based on recency and lifetime vaping, we constructed 12 definitions of experimenters versus more established or recent users. We examined how well each definition discriminated between experimenters and established/recent users based on correlates (eg, vaping dependence, harm perceptions) using multivariate tests of mean differences, controlling for multiple variables, and ratios of between- to within-group variance. Results: Four definitions best distinguished between experimenters and more established/recent users (ie, had greater Hotelling T2 statistics for the multivariate tests and higher ratios of between- to within-group variance). Three of these 4 identified experimenters as those with no past 30-day vaping. Conclusion: Ever vapers are not a monolithic group. Our results suggest that past 30-day use is an important criterion for distinguishing experimenters from more established users. Understanding nuances between user groups could lead to greater differentiation among ever vapers and aid campaign targeting.