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The research presented in this article is a systematic review of the literature on the assessment of mathematical modeling in the setting of mathematics education published in the previous five years. This research has compiled the current best information from around the world to offer an overview of the assessment of mathematical modeling for pre-service mathematics teachers or mathematics teachers. We followed the approach used in Joklitschke et al. (2021), which involved 10 steps in systematic literature review (SLR). We accessed using Web of Science (WoS), Scopus, and mathematics education journals that are ranked 1-10. Based on a full-text analysis of 18 peer-reviewed papers published in English, most of the research was conducted among pre-service mathematics teacher and most of the studies were conducted in Turkey, United States, and Germany. The future trends and opportunities were also discussed. We also found that most test types employed for measuring modeling competency were project, cognitive dimension, holistic approach, and the tests utilized more qualitative approach.

In 2020, Year 12 students at John Curtin College of the Arts, were required to model COVID-19 data from five different countries in order to find correlations between daily infections and unemployment rates, in order to make future predictions. Work received from students demonstrated how the task successfully provided unique learning opportunities, which are otherwise not experienced in a classroom environment under the pressures of a curriculum that is highly exam-focused and based on mechanistic algorithms. The paper also discusses some challenges faced and how they were overcome.

Background: Despite disproportionate rates of mental ill-health compared with non-Indigenous populations, few programs have been tailored to the unique health, social, and cultural needs and preferences of young Aboriginal and Torres Strait Islander males. This paper describes the process of culturally adapting the US-based Young Black Men, Masculinities, and Mental Health (YBMen) Project to suit the needs, preferences, culture, and circumstances of Aboriginal and Torres Strait Islander males aged 16–25 years in the Northern Territory, Australia. YBMen is an evidence-based social media-based education and support program designed to promote mental health, expand understandings of gender and cultural identities, and enhance social support in college-aged Black men. Methods: Our adaptation followed an Extended Stages of Cultural Adaptation model. First, we established a rationale for adaptation that included assessing the appropriateness of YBMen's core components for the target population. We then investigated important and appropriate models to underpin the adapted program and conducted a non-linear, iterative process of gathering information from key sources, including young Aboriginal and Torres Strait Islander males, to inform program curriculum and delivery. Results: To maintain program fidelity, we retained the core curriculum components of mental health, healthy masculinities, and social connection and kept the small cohort, private social media group delivery but developed two models: 'online only' (the original online delivery format) and 'hybrid in-person/online' (combining online delivery with weekly in-person group sessions). Adaptations made included using an overarching Aboriginal and Torres Strait Islander social and emotional wellbeing framework and socio-cultural strengths-based approach; inclusion of modules on health and wellbeing, positive Indigenous masculinities, and respectful relationships; use of Indigenous designs and colours; and prominent placement of images of Aboriginal and Torres Strait Islander male sportspeople, musicians, activists, and local role models. Conclusions: This process resulted in a culturally responsive mental health, masculinities, and social support health promotion program for young Aboriginal and Torres Strait Islander males. Next steps will involve pilot testing to investigate the adapted program's acceptability and feasibility and inform further refinement. Keywords: Aboriginal, Torres Strait Islander, Indigenous, Australia, male, cultural adaptation, social media, mental health, masculinities, social support. [ABSTRACT FROM AUTHOR]

Background: Early identification and treatment of chronic disease is associated with better clinical outcomes, lower costs, and reduced hospitalisation. Primary care is ideally placed to identify patients at risk of, or in the early stages of, chronic disease and to implement prevention and early intervention measures. This paper evaluates the implementation of a technological intervention called Future Health Today that integrates with general practice EMRs to (1) identify patients at-risk of, or with undiagnosed or untreated, chronic kidney disease (CKD), and (2) provide guideline concordant recommendations for patient care. The evaluation aimed to identify the barriers and facilitators to successful implementation. Methods: Future Health Today was implemented in 12 general practices in Victoria, Australia. Fifty-two interviews with 30 practice staff were undertaken between July 2020 and April 2021. Practice characteristics were collected directly from practices via survey. Data were analysed using inductive and deductive qualitative analysis strategies, using Clinical Performance - Feedback Intervention Theory (CP-FIT) for theoretical guidance. Results: Future Health Today was acceptable, user friendly and useful to general practice staff, and supported clinical performance improvement in the identification and management of chronic kidney disease. CP-FIT variables supporting use of FHT included the simplicity of design and delivery of actionable feedback via FHT, good fit within existing workflow, strong engagement with practices and positive attitudes toward FHT. Context variables provided the main barriers to use and were largely situated in the external context of practices (including pressures arising from the COVID-19 pandemic) and technical glitches impacting installation and early use. Participants primarily utilised the point of care prompt rather than the patient management dashboard due to its continued presence, and immediacy and relevance of the recommendations on the prompt, suggesting mechanisms of compatibility, complexity, actionability and credibility influenced use. Most practices continued using FHT after the evaluation phase was complete. Conclusions: This study demonstrates that FHT is a useful and acceptable software platform that provides direct support to general practice in identifying and managing patients with CKD. Further research is underway to explore the effectiveness of FHT, and to expand the conditions on the platform. [ABSTRACT FROM AUTHOR]

Aims: To elicit experiences of patients, family caregivers, and healthcare professionals in intermediate care units (IMCUs) in an academic medical centre in Baltimore, MD related to the challenges and intricacies of multimorbidity management to inform development of a multimorbidity symptom management toolkit. Design: Experience‐based co‐design. Methods: Between July and October 2021, patients aged 55 years and older with multimorbidity admitted to IMCUs at an academic medical centre in Baltimore, Maryland, USA were recruited and interviewed in person. Interdisciplinary healthcare professionals working in the IMCU were interviewed virtually. Participants were asked questions about their role in recognizing and treating symptoms, factors affecting the quality of life, symptom burden and trajectory over time, and strategies that have and have not worked for managing symptoms. An inductive thematic analysis approach was used for analysis. Results: Twenty‐three interviews were conducted: 9 patients, 2 family caregivers, and 12 healthcare professionals. Patients' mean age was 67.5 (±6.5) years, over half (n = 5) were Black or Hispanic, and the average number of comorbidities was 3.67. Five major themes that affect symptom management emerged: (1) the patient–provider relationship; (2) open and honest communication; (3) accessibility of resources during hospitalization and at discharge; (4) caregiver support, training, and education; and (5) care coordination and follow‐up care. Conclusion: Patients, caregivers, and healthcare professionals often have similar goals but different priorities for multimorbidity management. It is imperative to identify shared priorities and target holistic interventions that consider patient and caregiver experiences to improve outcomes. Implications for the Profession and/or Patient Care and Impact: This paper addresses the paucity of research related to the shared experience of disease trajectory and symptom management for people living with multimorbidity. We found that patients, caregivers, and healthcare professionals often have similar goals but different care and communication priorities. Understanding differing priorities will help better design interventions to support symptom management so people with multimorbidity can have the best possible quality of life. Reporting Method: We have adhered to the Consolidated Criteria for Reporting Qualitative Studies (COREQ) guidelines in our reporting. Patient or Public Contribution: This study has been designed and implemented with patient and public involvement throughout the process, including community advisory board engagement in the project proposal phase and interview guide development, and member checking in the data collection and analysis phases. The method we chose, experience‐based co‐design, emphasizes the importance of engaging members of a community to act as experts in their own life challenges. In the coming phases of the study, the public will be involved in developing and testing a new intervention, informed by these qualitative interviews and co‐design events, to support symptom management for people with multimorbidity. [ABSTRACT FROM AUTHOR]

Statistical body shape models (SBSM) provide compact, flexible representations of body shape that can be implemented in design software. However, few SBSMs have been created to represent adults in supported seated postures that are relevant for the design of seated environments, and none has incorporated the effects of age. This paper presents an SBSM based on surface laser-scan data from 155 U.S. adults. The data were processed to obtain homologous mesh structure and symmetric geometry, and the processed data were statistically analysed using principal component analysis to obtain a compact representation of the data variance. Regression analysis was conducted to predict body size and shape from stature, body mass index, ratio of sitting height to stature, sex, and age. The resulting model allows rapid generation of realistic body models for applications, including product design, accommodation assessment, and safety system optimisation. The model is publicly accessible at HumanShape.org. Practitioner summary: This paper presents a statistical model that represents adult body shapes in a supported seated posture based on 3 D anthropometric measurements. This model is the first whole-body parametric model known to incorporate age effects based on data extending beyond 65 years of age. [ABSTRACT FROM AUTHOR]

Background: Deep learning methods, where models do not use explicit features and instead rely on implicit features estimated during model training, suffer from an explainability problem. In text classification, saliency maps that reflect the importance of words in prediction are one approach toward explainability. However, little is known about whether the salient words agree with those identified by humans as important. Objectives: The current study examines in‐line annotations from human annotators and saliency map annotations from a deep learning model (ELECTRA transformer) to understand how well both humans and machines provide evidence for their assigned label. Methods: Data were responses to test items across a mix of United States subjects, states, and grades. Humans were trained to annotate responses to justify a crisis alert label and two model interpretability methods (LIME, Integrated Gradients) were used to obtain engine annotations. Human inter‐annotator agreement and engine agreement with the human annotators were computed and compared. Results and Conclusions: Human annotators agreed with one another at similar rates to those observed in the literature on similar tasks. The annotations derived using the integrated gradients (IG) agreed with human annotators at higher rates than LIME on most metrics; however, both methods underperformed relative to the human annotators. Implications: Saliency map‐based engine annotations show promise as a form of explanation, but do not reach human annotation agreement levels. Future work should examine the appropriate unit for annotation (e.g., word, sentence), other gradient based methods, and approaches for mapping the continuous saliency values to Boolean annotations. Lay Description: What is known about subject matter: Explainability of deep learning models is complicated by their large size, design, and complexity.Explainability methods in deep learning exist but have not been rigorously tested.Saliency maps, as a form of explainability, can be used to generate engine annotations.Human annotations can serve as basis for comparison. What paper adds to knowledge: How well human annotations work in one domain (crisis paper identification).How well two engine annotation methods match human annotations. Implications of study findings: Human annotations have reasonable reliability.Engine annotations have lower reliability than humans.Model‐based engine annotations perform better than model‐agnostic engine annotations. [ABSTRACT FROM AUTHOR]

Background: Teachers often rely on the use of open‐ended questions to assess students' conceptual understanding of assigned content. Particularly in the context of mathematics; teachers use these types of questions to gain insight into the processes and strategies adopted by students in solving mathematical problems beyond what is possible through more close‐ended problem types. While these types of problems are valuable to teachers, the variation in student responses to these questions makes it difficult, and time‐consuming, to evaluate and provide directed feedback. It is a well‐studied concept that feedback, both in terms of a numeric score but more importantly in the form of teacher‐authored comments, can help guide students as to how to improve, leading to increased learning. It is for this reason that teachers need better support not only for assessing students' work but also in providing meaningful and directed feedback to students. Objectives: In this paper, we seek to develop, evaluate, and examine machine learning models that support automated open response assessment and feedback. Methods: We build upon the prior research in the automatic assessment of student responses to open‐ended problems and introduce a novel approach that leverages student log data combined with machine learning and natural language processing methods. Utilizing sentence‐level semantic representations of student responses to open‐ended questions, we propose a collaborative filtering‐based approach to both predict student scores as well as recommend appropriate feedback messages for teachers to send to their students. Results and Conclusion: We find that our method outperforms previously published benchmarks across three different metrics for the task of predicting student performance. Through an error analysis, we identify several areas where future works may be able to improve upon our approach. Lay Description: What is already known about this topic: Open‐ended questions are used by teachers in the domain of mathematics to assess their students understanding but automated support for these types of questions are limited in online learning platforms. Recent advancements in areas of machine learning and natural language processing have led to promising results in a range of domains and applications. What this paper adds: Emulating how teachers identify similar student answers can be used to build tools that support teachers in assessing and providing feedback to student open‐ended work. Implications for practice: Developing better automated supports can increase the amount of direct feedback students receive to guide their learning. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Multicultural Counseling & Development is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Researchers are often faced with evaluating the effect of a policy or program that was simultaneously initiated across an entire population of units at a single point in time, and its effects over the targeted population can manifest at any time period afterwards. In the presence of data measured over time, Bayesian time series models have been used to impute what would have happened after the policy was initiated, had the policy not taken place, in order to estimate causal effects. However, the considerations regarding the definition of the target estimands, the underlying assumptions, the plausibility of such assumptions, and the choice of an appropriate model have not been thoroughly investigated. In this paper, we establish useful estimands for the evaluation of large-scale policies. We discuss that imputation of missing potential outcomes relies on an assumption which, even though untestable, can be partially evaluated using observed data. We illustrate an approach to evaluate this key causal assumption and facilitate model elicitation based on data from the time interval before policy initiation and using classic statistical techniques. As an illustration, we study the Hospital Readmissions Reduction Program (HRRP), a US federal intervention aiming to improve health outcomes for patients with pneumonia, acute myocardial infraction, or congestive failure admitted to a hospital. We evaluate the effect of the HRRP on population mortality among the elderly across the US and in four geographic subregions, and at different time windows. We find that the HRRP increased mortality from pneumonia and acute myocardial infraction across at least one geographical region and time horizon, and is likely to have had a detrimental effect on public health. [ABSTRACT FROM AUTHOR]

Health care providers have highlighted the need for tools and resources that support promotion of exercise behavior within comprehensive multiple sclerosis (MS) care. This study involved a final quality improvement evaluation of exercise promotion models and materials for inclusion within this setting. Our research team distributed a paper-based survey containing Likert scales, open answer questions, and copies of the models for editing. We distributed this survey among health care providers across the United States. We conducted a novel mixed-methods analysis evaluating quantitative, qualitative, and creative data. We received completed surveys from 13 health care providers who strongly rated the clarity and applicability of the models and materials, and reported that no major improvements were necessary. The minor improvements were specific per comprehensive MS care center. The feedback indicated that the "Exercise in Medicine" models and materials are guides such that the processes should be integrated into real world practice by amending roles and responsibilities with the team members and structure per comprehensive MS care center. This paper presents finalized models and materials for exercise promotion within comprehensive MS care that are ready to be tested for feasibility and efficacy in a clinical trial. Health care providers require support to promote exercise within the context of comprehensive MS care. The practice models in this article provide guides regarding how to promote exercise in this context. Implementing these exercise promotion guides can reduce the burden of neurologists, and ensure patients receive exercise support from appropriate providers. These guides should be implemented within the context of each individual care center, and not as an explicit step by step guide as each care center is unique. [ABSTRACT FROM AUTHOR]

BACKGROUND: Currently, there is a need for models, methods, and tools that allow ergonomics/human factor (E/HF) practitioners to assess the level of E/HF integration into organizations from a macroergonomics perspective. OBJECTIVE: This paper aims to propose the Ergonomic Maturity Model (EMM) and the tools for its application as a framework for integrating E/HF in organizations. METHODS: The EMM is a macroergonomic tool that allows stakeholders to evaluate the degree of development and integration of E/HF in the organization based on a participatory and macroergonomic approach. The EMM classifies organizations into five gradual levels of maturity: Ignorance, Understanding, Experimentation, Regular use, and Innovation. RESULTS: In this paper, we provide a three-stage procedure for guiding the application of the EMM: preparation of the evaluation, evaluation, and improvement plan and implementation. We include four tools developed specifically for applying EMM in organizations: evaluation matrix, weighting questionnaire, quick questionnaire, and prioritization matrix. Also, we present a Colombian floriculture company's case study to exemplify the use of the EMM. CONCLUSIONS: The EMM provides a framework for integrating E/HF into organizations from the macroergonomics approach. E/HF practitioners can find in the EMM a tool to help them channel the actions taken by the different organizational actors to improve the safety, health, well-being, and performance of work systems. Finally, it should be noted that further studies on the reliability and validity of the EMM are needed, which would contribute to demonstrating that the EMM can effectively and successfully guide change in E/HF maturity levels in organizations. [ABSTRACT FROM AUTHOR]

With the growing prevalence of chronic conditions driving 85% of all healthcare costs, digital health offers a promising opportunity to reverse disease and improve health at-scale. The healthcare industry's predominant approach to behavior change is performance-based with a focus on goals and tracking. This has not reversed the epidemic of chronic diseases and also can harm chronically ill and vulnerable patients via perceived failure-induced loss of motivation. Still nascent, the digital health industry is uniquely positioned to adopt and scale new and better behavior change approaches. In this paper, we present the theoretical foundation and initial findings of a neuroscience-based behavior change approach—what we call the Iterative Mindset MethodTM. We discuss its promise, as a potentially more effective, neuroscience-based approach to changing health behaviors long-term, particularly in vulnerable populations. We conclude with avenues for future research. [ABSTRACT FROM AUTHOR]

This paper provides an alternative approach to penalized regression for model selection in the context of high‐dimensional linear regressions where the number of covariates is large, often much larger than the number of available observations. We consider the statistical significance of individual covariates one at a time, while taking full account of the multiple testing nature of the inferential problem involved. We refer to the proposed method as One Covariate at a Time Multiple Testing (OCMT) procedure, and use ideas from the multiple testing literature to control the probability of selecting the approximating model, the false positive rate, and the false discovery rate. OCMT is easy to interpret, relates to classical statistical analysis, is valid under general assumptions, is faster to compute, and performs well in small samples. The usefulness of OCMT is also illustrated by an empirical application to forecasting U.S. output growth and inflation. [ABSTRACT FROM AUTHOR]

Purpose/Objective: Individuals with historically oppressed identities, such as disabled or racialized minorities, face inequities across all societal institutions, including education, criminal justice, and healthcare. Systems of oppression (e.g., ableism, racism) lead to inequities that have ultimately contributed to disproportionate rates of COVID-19 morbidity and mortality in the United States. In the midst of the COVID-19 pandemic, increased public attention regarding police brutality toward Black people and the reinvigoration of the national Black Lives Matter (BLM) movement further highlighted the detrimental effects of oppressive systems and the urgent need to promote equity in the United States. The disproportionate number of COVID-19-related deaths and police brutality are inextricably connected, as both are products of oppression toward minoritized communities. The co-occurrence of the pandemic and BLM movement protests also creates an opportunity for critical discourse on the intersection of ableism and anti-Black racism specifically within the field of rehabilitation psychology. Research Method/Design: The overarching goals of this review are to apply the Intersectional Ecological Model with the addition of the chronosystem to illustrate how systems of oppression lead to health disparity in COVID-19 survivorship and to provide recommendations to promote health equity. Conclusions/Implication: As the COVID-19 pandemic shifts to an endemic and efforts to eliminate oppressive systems continue, rehabilitation psychologists have an ongoing, evolving, and shared responsibility to employ socially-responsive solutions to promote optimal functioning for patients, families, and communities. Impact and Implications: Disabled and Black communities continue to face inequities across all societal systems. The COVID-19 pandemic and simultaneous Black Lives Matter Movement protests brought systemic inequities faced by disabled and Black communities to the forefront of the nation's attention, creating an opportunity to explore the intersection of ableism and anti-Black racism on COVID-19 survivorship. This paper uses the Intersectional Ecological Model to illustrate how systemic oppression contributes to inequity in COVID-19 survivorship for Black disabled communities. Rehabilitation psychologists can leverage the information in this paper to foster socially conscious clinical practice, research, training, and advocacy. [ABSTRACT FROM AUTHOR]

This paper considers the relationship between income and wealth using data from three sources: the Survey of Consumer Finances (SCF), the IRS and Forbes Magazine. Because of the legal and ethical constraints on the use of some of these data, the focus of the paper is limited to a few issues that are relevant to improving the design of the SCF and understanding better the quality of the information collected. The most important goal of the paper is estimation of functional relationships between income and wealth. Work to this end results in model predictions that are more effective than using income alone as a proxy for wealth. However, it is clear that the relationship is not strong, and more work is needed, particularly to address the noise introduced into the relationship by year-to-year income variability. [ABSTRACT FROM AUTHOR]

A documentary review was carried out on producing and publishing research papers on studying differential equations, mathematical models, and education. The bibliometric analysis proposed in this paper was to know the main characteristics of the volume of publications registered in the Scopus database during 2017-2021, identifying 90 publications. The information provided by the said platform was organized employing tables and figures categorizing the information by Year of Publication, Country of Origin, Area of Knowledge and Type of Publication. Once these characteristics were described, a qualitative analysis was used to refer to the position of different authors on the proposed topic. Among the main findings of this research, it is found that the United States, with 13 publications, was the country with the highest scientific production registered in the name of authors affiliated with institutions of that nation. The area of knowledge that made the greatest contribution to the construction of bibliographic material referring to the study of differential equations, mathematical models, and education was Mathematics, with 37 published documents, and the type of publication that was most used during the period mentioned above was the conference article, which represents 47% of the total scientific production. [ABSTRACT FROM AUTHOR]

Background: There is an increasing number of technological resources available to speech and language therapists (SLTs) for use in clinical practice, but the factors that influence SLTs' selection and use of such resources are not well understood. In related fields, technology acceptance models have been employed to explain users' adoption of technology and to inform the advancement of empirically supported technological resources. Aims: To determine the factors that influence SLTs' use of technology for clinical practice by testing a model of their technology acceptance and use. Methods & Procedures: We surveyed 209 practising SLTs in the United States representative of the speech and language membership of the American Speech–Language–Hearing Association (ASHA). Participants completed a 38‐item electronic survey representing four categories: (1) technology use, (2) technology attitudes and factors influencing technology use, (3) employment information and (4) demographics. Items measuring technology attitudes served as indicators of the research model, which mapped the primary relationships of a technology acceptance model. Survey data were collected before the Covid‐19 pandemic. Outcomes & Results: The research model accounted for 66% of the variance in SLTs' behavioural intention to use technology, which significantly and positively predicted the amount of time they reportedly spent using technology in the workplace. Subjective norms and attitudes towards technology use directly predicted the intention to use technology. Perceived usefulness and ease of use indirectly predicted intention to use technology. Survey respondents reported using technology during 48% (SD = 24%) of their overall weekly work hours on average, with a large majority reporting using technology at least once per week for planning (89% of respondents), assessment (66% of respondents) or intervention (90% of respondents). Conclusions & Implications: These findings statistically explain the relationships between SLTs' attitudes and their intention to use technology for clinical practice, contributing to our understanding of why SLTs adopt certain technologies. We also detail the nature and frequency of technology use in the clinical practice of SLTs. Future directions for this work include further exploring use categories, employing direct measurements of technology use and exploring the impact of recent changes in SLT service delivery due to the Covid‐19 pandemic on SLTs' technology attitudes. What this paper addsWhat is already known on the subjectExisting research about the adoption and use of technological resources by SLTs indicates that they select tools based on convenience, cost and recommendations by others.What this paper adds to existing knowledgeThis study is the first to develop and test a research model of SLTs' technology attitudes. The findings from model testing demonstrate the significant predictors of SLTs' behavioural intention to use technology for clinical purposes. Intent of use is related to how much SLTs use technology in the workplace.What are the potential or actual clinical implications of this work?The present findings can inform interventions targeting the design and adoption of electronic SLT resources that are empirically supported. [ABSTRACT FROM AUTHOR]

Medical legal partnerships address individual legal needs that can create impediments to health. Little is known about outcomes from medical legal partnerships and their relationship to access to justice. This paper reports outcomes from one medical legal partnership from the perspective of the client, with specific emphasis on impact on health and concepts related to access to justice. We suggest a conceptual model for incorporating medical legal partnerships into a broader framework about access to justice. [ABSTRACT FROM AUTHOR]

INTRODUCTION This study aims to assess the relationship between use of tobacco products and taste and smell disorders. METHODS A secondary dataset analysis of cross-sectional data from the National Health Interview Survey (NHIS) 2021 survey cycle, a nationally representative annual cross-sectional interview of non-institutionalized US civilians, was used. Participants' senses of smell and taste are assessed using self-reported questions. Participants were categorized into five groups based on their tobacco use: nontobacco users; cigarettes only; e-cigarettes only; cigar, pipe, or smokeless tobacco; and poly-tobacco product users. Disorders were defined as any self-reported difficulty in smelling, tasting, or reporting unpleasant odors or persistent tastes. Weighting procedures were used to estimate the national prevalence of taste, smell, and other disorders, stratified by tobacco products used. Adjusted logistic regression models were used to determine the association between tobacco products used and taste or smell compared to non-tobacco users. RESULTS A total of 40.2 million US adults reported experiencing smell or taste disorders. Nearly one in 10 adults reported a taste disorder (9.8%), and 13.4% indicated a smell disorder. The prevalence of taste or smell disorder was higher among females (17.5%), Hispanics (19.5%), individuals identified as 'other' racial minorities (21.1%), and lower income groups (21%). Compared to non-tobacco users, the highest odds of experiencing smell or taste disorders were among poly-tobacco product users (adjusted odds ratio, AOR=1.44; 95% CI: 1.31-1.58), followed by e-cigarette-only users (AOR=1.38; 95% CI: 1.02-1.87), cigarette-only smokers (AOR=1.17; 95% CI: 1.04-1.32), and users of cigars, pipes, or smokeless tobacco (AOR=1.15; 1.00; and 1.33; respectively). CONCLUSIONS Tobacco product use was associated with an increased risk of smell and taste disorders. The rising use of e-cigarettes among adolescents and young adults is particularly concerning given the limited understanding of the sensory effects of e-cigarettes and their growing popularity among younger populations. The study findings highlight the need for interventions aimed at reducing tobacco use of all kinds. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Assisted Learning is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: In the United States chronic illnesses have become a way of life for multiple generations – they are the number one cause of death and disability (accounting for more than 70% of deaths), 60% of American adults have at least one chronic disease, and 40% have multiple chronic conditions. Although multiple factors contribute to the growth in chronic disease prevalence, a major factor has been overreliance on health care systems for promoting health and preventing disease. Large health care systems are ill equipped for this role since they are designed to detect, treat, and manage disease, not to promote health or address the underlying causes of disease. Methods: Improving health outcomes in the U.S. will require implementing broad‐based prevention strategies combining biological, behavioral, and societal variables that move beyond clinical care. According to community medicine, clinical care alone cannot create, support, or maintain health. Rather, health can only ensue from combining clinical care with epidemiology and community organization, because health is a social outcome resulting from a combination of clinical science, collective responsibility, and informed social action. Results: During the past 20 years, our team has developed an operational community medicine approach known as community health science. Our model provides a simple framework for integrating clinical care, population health, and community organization, using community‐based participatory research (CBPR) practices for developing place‐based initiatives. In the present paper, we present a brief overview of the model and describe its evolution, applications, and outcomes in two major urban environments. Conclusion: The paper demonstrates means for integrating the social determinants of health into collaborative place‐based approaches, for aligning community assets and reducing health disparities. It concludes by discussing how asset‐based community development can promote social connectivity and improve health, and how our approach reflects the emerging national consensus on the importance of place‐based population system change. [ABSTRACT FROM AUTHOR]

Background: Since spring 2013, periodic emergence of avian influenza A(H7N9) virus in China has heightened the concern for a possible pandemic outbreak among humans, though it is believed that the virus is not yet human-to-human transmittable. Till June 2017, A(H7N9) has resulted in 1533 laboratory-confirmed cases of human infections causing 592 deaths. The aim of this paper is to present disease burden estimates (measured by infection attack rates (IAR) and number of deaths) in the event of a possible pandemic outbreak caused by human-to-human transmission capability acquired by A(H7N9) virus. Even though such a pandemic will likely spread worldwide, our focus in this paper is to estimate the impact on the United States alone.Method: The method first uses a data clustering technique to divide 50 states in the U.S. into a small number of clusters. Thereafter, for a few selected states in each cluster, the method employs an agent-based (AB) model to simulate human A(H7N9) influenza pandemic outbreaks. The model uses demographic and epidemiological data. A few selected non-pharmaceutical intervention (NPI) measures are applied to mitigate the outbreaks. Disease burden for the U.S. is estimated by combining results from the clusters applying a method used in stratified sampling.Results: Two possible pandemic scenarios with R 0 = 1.5 and 1.8 are examined. Infection attack rates with 95% C.I. (Confidence Interval) for R 0 = 1.5 and 1.8 are estimated to be 18.78% (17.3-20.27) and 25.05% (23.11-26.99), respectively. The corresponding number of deaths (95% C.I.), per 100,000, are 7252.3 (6598.45-7907.33) and 9670.99 (8953.66-10,389.95).Conclusions: The results reflect a possible worst-case scenario where the outbreak extends over all states of the U.S. and antivirals and vaccines are not administered. Our disease burden estimations are also likely to be somewhat high due to the fact that only dense urban regions covering approximately 3% of the geographic area and 81% of the population are used for simulating sample outbreaks. Outcomes from these simulations are extrapolated over the remaining 19% of the population spread sparsely over 97% of the area. Furthermore, the full extent of possible NPIs, if deployed, could also have lowered the disease burden estimates. [ABSTRACT FROM AUTHOR]

U.S. organizations seek to provide interns with positive socialization experiences such that their internships may lead to job offer acceptances. This study presents a process model examining how developmental relationships shape interns' experiences and outcomes. Utilizing a sample of 6,802 recent graduates from across 200 U.S. colleges and universities who completed an internship, the study found that supervisor support indirectly influences an intern's decision to accept a job offer through learning and intern satisfaction. Findings further show that interns benefit from developmental relationships such as mentors since mentor status buffered the decrements in learning when supervisor support was low. This study contributes to the growing internship literature that draws upon early socialization and newcomer adaptation by examining the critical role developmental relationships play in the experiences of interns. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to describe and discuss both the early implementation of a US mental health intervention for young children in the context of its introduction to a pilot site in a London borough and the progress made in establishing a randomised controlled trial (RCT). Design/methodology/approach: This paper describes an evaluation of a new intervention and the learning that followed in terms of its implementation and future evaluation. Qualitative data were collected from a range of stakeholders and practitioners through interviews and small group discussions. These interviews focussed on both of these issues, with particular reference to the proposal to conduct an RCT. Findings: The findings of this evaluation add to the evidence on how best to support new initiatives that have been introduced from other settings and countries to embed in a receiving site and the optimal timing and feasibility of conducting an RCT. At the end of the feasibility study, which took place within the year of the service being introduced and which was only open to clients for six months of this year the conclusion was that an RCT at that point was neither possible nor desirable. Over the following years, the commitment of the judiciary to examine if there was a way to make an RCT study in respect of this intervention meant that a template was established that may well have broader application. Research limitations/implications: At a time when there is an increasing demand for evidence on effective interventions this paper makes a valuable contribution to the development of RCTs in general and specifically in the family court arena. It also recommends that attention must also be paid to the time, which is needed to implement and establish interventions and then to test them. Practical implications: This paper highlights the need to establish realistic timescales not only around the implementation of initiatives but also for their evaluation. Originality/value: This study breaks new ground in considering implementation challenges in the court and children's services' context. It brings to the fore the important role of the judiciary in approving new processes. [ABSTRACT FROM AUTHOR]

This paper presents findings from a qualitative study exploring how students at a university in the southern USA conceptualize, theorize, and attempt to influence the role 'social factors' play in mental illness and well-being. Drawing on models of research co-production and principles of critical pedagogy, a group of 10 university students ('student researchers') worked with a faculty member to develop and conduct the study. The results highlight three ways in which the student interviewees ('student interlocutors') theorize 'the social'. The first two – (1) via the 'social determinants of health' and (2) by means of theories on 'neoliberal subjectivity' – provide a powerful frame for interrogating hierarchical systems of power. However, because neither of these corresponds to our interest in producing knowledge for social change, we used prefigurative and speculative approaches to explore a third notion of the social, that of (3) 'world-making practices'. We conclude by reflecting on the relevance of this project for educators, learners, and researchers seeking to deepen knowledge and theories of the social in mental health. We argue that co-produced research that draws from principles of critical pedagogy can enhance interdisciplinary collaboration and lead to more nuanced, transformative, and innovative analyses. [ABSTRACT FROM AUTHOR]

Research has established a link between Adverse Childhood Experiences (ACEs) and mental health difficulties across the lifespan. This includes recent research that linked ACEs to lower hope in adulthood. To better understand the link between ACEs and lower hope, the current study tested a model, based in both attachment and hope theory, of ACEs as a driver of lower hope via lower attachment security as a mediator. To test the theorized linear relationship between variables, among a sample of U.S. adults (N' = 293), the study employed established measures of ACEs, attachment style, and hope. A 3 variable path model with full mediation model was hypothesized, with ACEs driving lower attachment security that is linked to lower hope. The model was tested with structural equation modeling (SEM). The results indicated the theory proposed full mediation model fit the data well (Χ2 = 102.0, df = 52; p <.001; RMSEA =.057 [90% CI:.041,.074]; CFI:.96; SRMR:.053), with the model indicating ACEs drove attachment insecurity (R2 =.125) that generated lower hope (R2 =.208). A subsequent bootstrapping analysis (n = 5,000) validated the full mediation model. Multigroup analyses also indicated the model was stable across demographic groups. The paper concludes with a discussion of the implications of the results, including how the data suggests a need for further research into interventions for ACE survivors to promote attachment security and hope. [ABSTRACT FROM AUTHOR]

In today's highly competitive world market, businesses can hardly maintain their competitiveness without strong innovation abilities. In the past, many Chinese enterprises have enjoyed success through imitation. But to continue to succeed in a global marketplace, they must develop ambidextrous innovation abilities. The resource‐based theory eloquently posits that competitive advantage is associated with different and heterogeneous resources. To obtain such resources, firms must establish an external network to acquire necessary knowledge and skills. In this paper, we develop a theoretical model linking network orientation, organisational improvisation, ambidexterity and competitive tension. We postulate that organisational improvisation has a mediating effect and competitive tension is a moderator. Empirical results (N = 340) show that (1) network orientation leads to both exploratory and exploitative innovations, (2) the above effect is mediated by organisational improvisation and (3) competitive tension positively moderates the effect between network orientation and organisational improvisation. [ABSTRACT FROM AUTHOR]

Thousands of people are reported lost in the wilderness in the United States every year and locating these missing individuals as rapidly as possible depends on coordinated search and rescue (SAR) operations. As time passes, the search area grows, survival rate decreases, and searchers are faced with an increasingly daunting task of searching large areas in a short amount of time. To optimize the search process, mathematical models of lost person behavior with respect to landscape can be used in conjunction with current SAR practices. In this paper, we introduce an agent-based model of lost person behavior which allows agents to move on known landscapes with behavior defined as independent realizations of a random variable. The behavior random variable selects from a distribution of six known lost person reorientation strategies to simulate the agent's trajectory. We systematically simulate a range of possible behavior distributions and find a best-fit behavioral profile for a hiker with the International Search and Rescue Incident Database. We validate these results with a leave-one-out analysis. This work represents the first time-discrete model of lost person dynamics validated with data from real SAR incidents and has the potential to improve current methods for wilderness SAR. [ABSTRACT FROM AUTHOR]

The integration of medical schools and clinical partners is effectively established through the formation of academic medical centers (AMCs). The tripartite mission of AMCs emphasizes the importance of providing critical clinical services, medical innovation through research, and the education of future health care leaders. Although AMCs represent only 5% of all hospitals, they contribute substantially to serving disadvantaged populations of patients, including an estimated 37% of all charity care and 26% of all Medicaid hospitalizations. Currently, most AMCs use a business model centered upon revenue generated from hospital services and/or practice plans. In the last decade, mounting financial demands have placed significant pressure on AMC finances because of the rising costs associated with complex clinical care and operating diverse graduate medical education programs. A shift toward population health-centric health care management strategies will profoundly influence the predominant forms of health care delivery in the United States in the foreseeable future. Health systems are increasingly pursuing new strategies to manage financial risk, such as forming Accountable Care Organizations and provider-sponsored plans to provide value-based care. Refocusing research and operational capacity toward population health management fosters collaboration and enables reintegration with hospital and clinical partners across care networks, and can potentially create new revenue streams for AMCs. Despite the benefits of population health integration, current literature lacks a blueprint to guide AMCs in the transformation toward sustainable population health management models. The purpose of this paper is to propose a modern conceptual framework that can be operationalized by AMCs in order to achieve a sustainable future. [ABSTRACT FROM AUTHOR]

Copyright of Family Process is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose Mental health providers will be increasingly called on to lead psychiatric efforts to improve care and care redesign. The Accreditation Council for Graduate Medical Education (ACGME) in the USA requires residency programs to teach quality improvement (QI) and systems-based practice (SBP) to all trainees as part of training requirements. However, teaching QI and SBP concepts without a clinical context can be challenging with low trainee engagement. The paper aims to discuss these issues.Design/methodology/approach The authors describe curricular redesign with a specialized educator faculty task force that aimed to create a longitudinal curriculum that integrated abstract QI concepts into clinical practice settings, and helped trainees apply SBP concepts throughout residency. In addition, the authors describe the utilization of resident prescriber profiles to contextualize clinical practice habits, and the implementation of an educational case conference series with emphasis on QI-specific educational tools such as root cause analysis (RCA).Findings Formal resident feedback from 2016 to 2018 has demonstrated improved trainee satisfaction. The resulting curricular change has also led to a new chief resident role and sustained engagement in QI and SBP education by trainees.Research limitations/implications The faculty task force and curricular design changes described in this paper were implemented at one large academic institution. Thus, additional assessment and research is necessary to address the generalizability of the interventions described.Originality/value Since QI and SBP are becoming more prominent requirements for medical education accrediting bodies such as the ACGME, the innovative curricular design can benefit other residency and medical student education programs that attempt to integrate clinical practice with education incorporating QI and SBP concepts. [ABSTRACT FROM AUTHOR]

Objectives: The US Food and Drug Administration has expressed interest in using mathematical models to evaluate potential tobacco policies. The goal of this systematic review was to synthesize data from tobacco control studies that employ mathematical models.Methods: We searched five electronic databases on July 1, 2013 to identify published studies that used a mathematical model to project a tobacco-related outcome and developed a data extraction form based on the ISPOR-SMDM Modeling Good Research Practices. We developed an organizational framework to categorize these studies and identify models employed across multiple papers. We synthesized results qualitatively, providing a descriptive synthesis of included studies.Results: The 263 studies in this review were heterogeneous with regard to their methodologies and aims. We used the organizational framework to categorize each study according to its objective and map the objective to a model outcome. We identified two types of study objectives (trend and policy/intervention) and three types of model outcomes (change in tobacco use behavior, change in tobacco-related morbidity or mortality, and economic impact). Eighteen models were used across 118 studies.Conclusions: This paper extends conventional systematic review methods to characterize a body of literature on mathematical modeling in tobacco control. The findings of this synthesis can inform the development of new models and the improvement of existing models, strengthening the ability of researchers to accurately project future tobacco-related trends and evaluate potential tobacco control policies and interventions. These findings can also help decision-makers to identify and become oriented with models relevant to their work. [ABSTRACT FROM AUTHOR]

The purpose of this study is to explore the nature of the association and the possible existence of a shortrun and long-run relationship between the stock-market indices of South Africa, India and the USA. The idea behind this combination is to know how the stock markets of these three prominent countries are related to each other. The study employs monthly data from the stock indices, namely JALSH (South Africa), NIFTY (India) and NASDAQ (USA) composite from April 2004 to March 2014. After testing for the normality of the data distribution and the stationarity of the time series data, this paper discovered a strong correlation between the stock market indices of South Africa, India and the USA. The correlation among the stock markets is high, particularly between South Africa and India. In addition, the paper attempts to discover the presence of any predictive ability among these markets by applying the Granger causality test. The result indicates that the NASDAQ index has no predictive ability as far as the JALSH and NIFTY indices are concerned. However, the JALSH index has a predictive ability on the NIFTY index. After testing the Granger cause relationship, the existence of a long-run and short-run relationship is tested. The long-run relationships among the stock market indices are analysed, following the Johansen and Juselius multivariate cointegration approach. The result suggests the absence of a long-run relationship among the three stock market indices. Short-run relationship is investigated with the Vector Autoregression (VAR) model, and the outcome obtained shows that both the USA and the South African stock markets are predicted only by their own past lags. However, the Indian stock market is seen to be a function of its own past lags and the past lags of the South African stock index. [ABSTRACT FROM AUTHOR]

This paper derives the value and risk of aggregate human capital in a stochastic equilibrium model with Duffie-Epstein preferences. A three-factor asset-pricing model is derived, where the factors are the market, the capital share, and investment in human capital. When the model is calibrated to match the historical ratio of wages to consumption in the United States, the weight of human capital in aggregate wealth is estimated to be about 93%, well above most previous estimates, and human capital's riskiness is lower than that of the market portfolio. [ABSTRACT FROM AUTHOR]

Visceral leishmaniasis (VL), one of the deadliest parasitic diseases in the world, causes more than 50,000 human deaths each year and afflicts millions of people throughout South America, East Africa, South Asia, and Mediterranean Region. In 2015 the World Health Organization classified VL as a neglected tropical disease (NTD), prompting concentrated study of the VL epidemic using mathematical and simulation models. This paper reviews literature related to prevalence and prevention control strategies. More than thirty current research works were reviewed and classified based on VL epidemic study methods, including modeling approaches, control strategies, and simulation techniques since 2013. A summarization of these technical methods, major findings, and contributions from existing works revealed that VL epidemic research efforts must improve in the areas of validating and verifying VL mathematical models with real-world epidemic data. In addition, more dynamic disease control strategies must be explored and advanced simulation techniques must be used to predict VL pandemics. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to critically examine school health education in the USA and present alternative approaches for more critical and comprehensive health education.Design/methodology/approach An ecological model framework is used to identify the limitations and opportunities for improvement in school health education in the USA. An argument is made for school health education that embraces ecological approaches, political economy theory, and critical pedagogies.Findings US schools have been tasked with providing health education that is primarily rooted in individualistic approaches. Often missing from this education is recognition of the social and structural determinants of health that greatly influence one’s ability to practice the health behaviors promoted in schools. This raises pedagogical and ethical concerns, which can be addressed by teaching health education that is grounded in ecological and political economy understandings of health and in critical pedagogies that allow students to more comprehensively and accurately understand health, how their worlds influence health, and their agency within those worlds.Practical implications This paper offers justification for a critical model of school health education and for the professional preparation of school health educators that is grounded in critical pedagogy and ecological approaches.Originality/value This work complements other research on critical health education by adding explicit integration of the ecological model and the political economy theory within critical pedagogies. [ABSTRACT FROM AUTHOR]

Applying Andersen's health care utilization model, this paper shows the prevalence of immigrants' medical and dental tourism and associated factors. An analysis of the 2003 New Immigrant Survey data shows that about 17% of immigrants received medical care in a foreign country, whereas about one-third obtained dental care outside the United States. Latino immigrants have a higher prevalence of both types of tourism than their Asian counterparts. Race, level of education, and health insured status are commonly associated with medical and dental tourism. The findings contribute to the scarce literature on immigrants' health care utilization and medical and dental tourism. [ABSTRACT FROM AUTHOR]

To provide medical and social services to underserved communities, many health care organizations across the United States have expanded the role of emergency medical services to include mobile integrated health and community paramedicine (MIH-CP). Although MIH-CP programs differ in structure and setting, many share the common goal of improving health through home-based, patient-centered care management models. Ideally, these innovative programs reduce use of health care services, including 911 (US emergency system) calls and emergency department visits. In 2018 a large, urban academic medical center partnered with the city's fire department to establish an MIH-CP program to support patients as they transition in their first 30 days at home after hospitalization. Prior to launch, a multidisciplinary team developed a logic model to guide development, implementation, and evaluation of this complex and innovative program. This paper describes the team's structured process for developing a logic model. It also describes key components of the initial logic model and the Transitional Health Support program structure, as well as subsequent revisions to both. [ABSTRACT FROM AUTHOR]

Copyright of Policy Studies Journal is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Mental illness is an epidemic in the United States, and there is a gap in care due to minimal integrated programs and transitional community resources. This paper reports the development of a conceptual framework to identify challenges facing families living with mental illness and the integral role nursing plays to positively impact health. An inductive, bottom-up approach was used to develop the Nursing Science, Mental Illness and Family model. Concepts clustered around family health, cycle of suffering, improving outcomes, healthcare policy, and nursing science. Successful, goal-directed interprofessional collaborations are essential for individual-, family-, and system-level interventions to be effective. [ABSTRACT FROM AUTHOR]

Background: Over the past few decades, numerous forecasting methods have been proposed in the field of epidemic forecasting. Such methods can be classified into different categories such as deterministic vs. probabilistic, comparative methods vs. generative methods, and so on. In some of the more popular comparative methods, researchers compare observed epidemiological data from the early stages of an outbreak with the output of proposed models to forecast the future trend and prevalence of the pandemic. A significant problem in this area is the lack of standard well-defined evaluation measures to select the best algorithm among different ones, as well as for selecting the best possible configuration for a particular algorithm.Results: In this paper we present an evaluation framework which allows for combining different features, error measures, and ranking schema to evaluate forecasts. We describe the various epidemic features (Epi-features) included to characterize the output of forecasting methods and provide suitable error measures that could be used to evaluate the accuracy of the methods with respect to these Epi-features. We focus on long-term predictions rather than short-term forecasting and demonstrate the utility of the framework by evaluating six forecasting methods for predicting influenza in the United States. Our results demonstrate that different error measures lead to different rankings even for a single Epi-feature. Further, our experimental analyses show that no single method dominates the rest in predicting all Epi-features when evaluated across error measures. As an alternative, we provide various Consensus Ranking schema that summarize individual rankings, thus accounting for different error measures. Since each Epi-feature presents a different aspect of the epidemic, multiple methods need to be combined to provide a comprehensive forecast. Thus we call for a more nuanced approach while evaluating epidemic forecasts and we believe that a comprehensive evaluation framework, as presented in this paper, will add value to the computational epidemiology community. [ABSTRACT FROM AUTHOR]

Lung cancer, primarily non-small-cell lung cancer (NSCLC), is the leading cause of cancer deaths in the United States and worldwide. While early detection significantly improves five-year survival, there are no reliable diagnostic tools for early detection. Several exosomal microRNAs (miRs) are overexpressed in NSCLC, and have been suggested as potential biomarkers for early detection. The present paper develops a mathematical model for early stage of NSCLC with emphasis on the role of the three highest overexpressed miRs, namely miR-21, miR-205 and miR-155. Simulations of the model provide quantitative relationships between the tumor volume and the total mass of each of the above miRs in the tumor. Because of the positive correlation between these miRs in the tumor tissue and in the blood, the results of the paper may be viewed as a first step toward establishing a combination of miRs 21, 205, 155 and possibly other miRs as serum biomarkers for early detection of NSCLC. [ABSTRACT FROM AUTHOR]

BACKGROUND: Increased federal attention to advancing racial equity and support for underserved communities suggests the need for data on racial and ethnic differences in evidence-based employment services for people with serious mental illness. Individual Placement and Support (IPS) is an evidence-based model of supported employment for this population. OBJECTIVE: The objective was to identify differences based on race and ethnicity in IPS services. METHODS: This narrative review examined the empirical literature on IPS services in the U.S., assessing evidence of differences in access, retention, and effectiveness for Black and Hispanic IPS clients, relative to non-Hispanic Whites. RESULTS: We identified 12 studies examining racial and ethnic differences in access (4 studies), retention (3 studies), and effectiveness (6 studies). The findings for access to IPS were mixed, with two studies showing no differences, one finding less access for Blacks, and another finding greater access for Blacks but less access for Hispanics. Three studies found better retention rates for clients enrolled in IPS regardless of race or ethnicity. Compared to clients receiving usual vocational services, all studies found better employment outcomes for IPS clients regardless of race or ethnicity. CONCLUSION: Unlike for most of health care, few racial and ethnic differences have been found for IPS employment services in the U.S. Access to IPS is inadequate for all groups, with conflicting evidence whether Blacks and Hispanics have even less access. Based on the available evidence, Black and Hispanic clients have comparable retention and employment outcomes in IPS as non-Hispanic White clients. State and local mental health leaders responsible for monitoring IPS outcomes should routinely report statistics on race and ethnicity. They should also give active attention to client needs and equity. Research designs should answer multifaceted questions regarding disparities for historically underserved populations. [ABSTRACT FROM AUTHOR]

The perinatal period involves major developmental transitions which can be conceptualized through a biopsychosocial (BPS; Engel in Science 196:129–136, 1977, 10.1126/science.847460, in The American Journal of Psychiatry 137:535–544, 1980, 10.1176/ajp.137.5.535), systemic (von Bertalanffy, General system theory: Foundations, development, applications, George Braziller, New York, 1968) framework. Thus, no one domain of health in the perinatal period can be understood without exploring how the other domains are both impacted by and impacting the others. As a result of COVID-19, popular media is paying special attention to the biomedical domain of women in the perinatal period as it relates to health outcomes and changes in perinatal healthcare policies; however, considerably less attention is being paid to the other BPS health domains and systemic impacts. This paper will outline U.S. changes in healthcare as a result of the COVID-19 pandemic for individuals, couples, and families within the perinatal period (i.e., family planning and conception, prenatal, labor and delivery, and postpartum) and explore the unique psychosocial, systemic impacts. Recommendations for care, including telehealth and virtual support options, and future directions for research will be provided. [ABSTRACT FROM AUTHOR]

Objective: While international students frequently face behavioral health risks due to the stress of adjusting to new cultures, many demonstrate effective coping skills that minimize negative outcomes. The current study tested the mediating effects of resilience and mental health on the relationship between acculturative stress and binge drinking. Participants: International students (N = 322) in the United States. Methods: A cross-sectional design using both online and paper-based survey was implemented. Structural equation modeling was conducted to test the hypothesized mediation model. Results: The results showed good model fit, with resilience mediating the relationship between acculturative stress and binge drinking in the conceptual model. Conclusions: Behavioral health problems and needs of international students are prevalent themes in social work practice; this study, therefore, has practical implications for U.S. colleges and universities as they make decisions about programs and services. [ABSTRACT FROM AUTHOR]

This paper presents a systematic review of the quantitative HIV research that assessed the relationships between religion, spirituality, HIV syndemics, and individual HIV syndemics-related health conditions (e.g. depression, substance abuse, HIV risk) among men who have sex with men (MSM) in the United States. No quantitative studies were found that assessed the relationships between HIV syndemics, religion, and spirituality. Nine studies, with 13 statistical analyses, were found that examined the relationships between individual HIV syndemics-related health conditions, religion, and spirituality. Among the 13 analyses, religion and spirituality were found to have mixed relationships with HIV syndemics-related health conditions (6 nonsignificant associations; 5 negative associations; 2 positive associations). Given the overall lack of inclusion of religion and spirituality in HIV syndemics research, a conceptual model that hypothesizes the potential interactions of religion and spirituality with HIV syndemics-related health conditions is presented. The implications of the model for MSM's health are outlined. [ABSTRACT FROM AUTHOR]