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\"From the perspective of the tutor, teaching a language one-to-one is not just one more way of doing what classroom teachers do. With only one learner, it is possible to give serious attention to principles of second language acquisition such as motivation, error treatment, and learner autonomy, which are more difficult to address in classroom learning. One-on-One Language Teaching and Learning brings together a strong theoretical framework with practical suggestions and actual experiences of language learners and tutors from around the world. It applies research in the field of language acquisition and teaching to issues like building a strong tutor-student relationship, working with multilingual learners, and learning various skills and strategies. The book will be valuable for tutors of many languages, not only English, as well as learners who wants to take a more active role in one-on-one learning\"-- Provided by publisher.

Telehealth services that allow remote communication between the patient and the clinical team are an emerging part of care delivery. Given language barriers, patients with limited English proficiency present a unique set of challenges in integrating telehealth and ensuring equity. Using data from 84,419 respondents in the 2015-18 California Health Interview survey, we assessed the association between limited English proficiency and telehealth use (telephone and video visits) and evaluated the impact of telehealth use on health care access and use. We found that patients with limited English proficiency had lower rates of telehealth use (4.8 percent versus 12.3 percent) compared with proficient English speakers. In weighted multivariable logistic regression, patients with limited English proficiency still had about half the odds of using telehealth. Telehealth use was associated with increased emergency department use for all patients. This study suggests that policy makers and clinicians must focus on limited English proficiency as an important dimension to promote telehealth equity and decrease digital divides.

For individuals experiencing intimate partner violence (IPV), formal services, including community agencies, health services, or the criminal justice system, are critical resources. Understanding the specific barriers that hinder or prevent survivors from seeking help from formal services could reveal important implications for the development of services for IPV as well as for members of other organizations who encounter survivors. The authors conducted a systematic review of the literature to identify barriers to help-seeking from formal services for survivors. Ten electronic databases were searched for key terms related to IPV, help seeking from formal services, and barriers to help seeking. Articles were included in the review if they were U.S.-based, contained samples that were adults who had experienced IPV, and discussed barriers to seeking help from formal services. An initial search yielded 1,155 articles and after screening, 29 articles were included in the review. Data were extracted to reveal the state of the literature regarding help-seeking barriers for survivors. Six barriers to help seeking were identified as follows: (1) lack of awareness, (2) access challenges, (3) consequences of disclosure, (4) lack of material resources, (5) personal barriers, and (6) system failures. These findings demonstrate the need for continued education surrounding available services for IPV as well as the continued development of resources that can mitigate personal barriers that survivors may face. Furthermore, these findings illuminate the necessity to increase the access of services, particularly for non-English speakers, immigrants and refugees, individuals with disabilities, men, and LGBTQIA identified individuals.

Objectives. To determine the prevalence of COVID-19–related discrimination among major US racial/ethnic groups and estimate associations between discrimination, race/ethnicity, and other sociodemographic characteristics. Methods. We conducted a nationally representative online survey of 5500 American Indian/Alaska Native, Asian, Black/African American, Hawaiian/Pacific Islander, Latino (English and Spanish speaking), White, and multiracial adults from December 2020 to February 2021. Associations between sociodemographic characteristics and COVID-19–related discrimination were estimated via multinomial logistic regression. Results. A total of 22.1% of the participants reported experiencing discriminatory behaviors, and 42.7% reported that people acted afraid of them. All racial/ethnic minorities were more likely than White adults to experience COVID-19–related discrimination, with Asian and American Indian/Alaska Native adults being most likely to experience such discrimination (discriminatory behaviors: adjusted odd ratio [AOR] = 2.59; 95% confidence interval [CI] = 1.73, 3.89; and AOR = 2.67; 95% CI = 1.76, 4.04; people acting afraid: AOR = 1.54; 95% CI = 1.15, 2.07; and AOR = 1.84; 95% CI = 1.34, 2.51). Limited English proficiency, lower education, lower income, and residing in a big city or the East South Central census division also increased the prevalence of discrimination. Conclusions. COVID-19–related discrimination is common, and it appears that the pandemic has exacerbated preexisting resentment against racial/ethnic minorities and marginalized communities. Efforts are needed to minimize and discredit racially driven language and discrimination around COVID-19 and future epidemics. (Am J Public Health. 2022;112(3):453–466. https://doi.org/10.2105/AJPH.2021.306594 )

The concept of limited English proficiency (LEP) presents significant challenges when applied to the healthcare needs of the diverse and growing multilingual population in the U.S. We expound on the following ways in which the concept of LEP is problematic: the ethnocentric notion of a “primary language,” the ambiguous idea of “limited ability,” and the deficit-oriented construct of “language assistance.” We provide examples that illustrate the negative healthcare impact of LEP terminology, including the unaccounted-for complexities of health communication within the concept of “primary language,” the “limited abilities” of health professionals whose language skills are often unassessed, and the ignored role of “language assistance” resources such as interpreters as essential collaborators. Finally, we propose rethinking LEP by (a) reframing patient language using the term non-English language preference and (b) assessing health professional non-English language skills. These actionable strategies have the potential to improve language-appropriate healthcare for diverse populations.

Automatic diagnosis of depression based on speech can complement mental health treatment methods in the future. Previous studies have reported that acoustic properties can be used to identify depression. However, few studies have attempted a large-scale differential diagnosis of patients with depressive disorders using acoustic characteristics of non-English speakers. This study proposes a framework for automatic depression detection using large-scale acoustic characteristics based on the Korean language. We recruited 153 patients who met the criteria for major depressive disorder and 165 healthy controls without current or past mental illness. Participants' voices were recorded on a smartphone while performing the task of reading predefined text-based sentences. Three approaches were evaluated and compared to detect depression using data sets with text-dependent read speech tasks: conventional machine learning models based on acoustic features, a proposed model that trains and classifies log-Mel spectrograms by applying a deep convolutional neural network (CNN) with a relatively small number of parameters, and models that train and classify log-Mel spectrograms by applying well-known pretrained networks. The acoustic characteristics of the predefined text-based sentence reading automatically detected depression using the proposed CNN model. The highest accuracy achieved with the proposed CNN on the speech data was 78.14%. Our results show that the deep-learned acoustic characteristics lead to better performance than those obtained using the conventional approach and pretrained models. Checking the mood of patients with major depressive disorder and detecting the consistency of objective descriptions are very important research topics. This study suggests that the analysis of speech data recorded while reading text-dependent sentences could help predict depression status automatically by capturing the characteristics of depression. Our method is smartphone based, is easily accessible, and can contribute to the automatic identification of depressive states.

Chinese students represent a substantial portion of the UK university student population, with most of them being postgraduates. However, whilst the UK remains a top choice for Chinese students seeking to complete a higher degree programme, competition within the global Higher Education (HE) landscape is intensifying. Consequently, popular HE destinations such as the USA and the UK must now contend with growing academic markets in Australia and New Zealand (Marginson, 2006) as well as some non-English speaking countries which offer appealing university degrees through English-Medium-Instruction (EMI) (Mok, 2007). It is therefore salutary to ensure that Chinese students continue to find the UK appealing. This is vitally important both for the economy and the intellectual diversity and talents these students bring to UK HE institutions. This study thus revisits the core motives which drive Chinese students to UK universities. Significantly, unlike other investigations which have treated the topic of motivation rather marginally and through broad research scopes, this paper uses a 'small-lens approach' (Ushioda, 2016), which here is operationalised through the combination of practitioner research and narrative analysis. The study therefore focuses on a small group (N = 16) of Chinese students to unpack the nuances of meaning which characterise their initial motivation to study in Britain. (HRK / Abstract übernommen).

Digital consultations between patients and clinicians increased markedly during the COVID-19 pandemic, raising questions about equity. This study aimed to review the literature on how multiple disadvantage-specifically, older age, lower socioeconomic status, and limited English proficiency-has been conceptualized, theorized, and studied empirically in relation to digital consultations. We focused mainly on video consultations as they have wider disparities than telephone consultations and relevant data on e-consultations are sparse. Using keyword and snowball searching, we identified relevant papers published between 2012 and 2022 using Ovid MEDLINE, Web of Science, Google Scholar, and PubMed. The first search was completed in July 2022. Papers meeting the inclusion criteria were analyzed thematically and summarized, and their key findings were tabulated using the Grading of Recommendations Assessment, Development, and Evaluation Confidence in the Evidence from Reviews of Qualitative Research criteria. Explanations for digital disparities were critically examined, and a search was undertaken in October 2022 to identify theoretical lenses on multiple disadvantage. Of 663 articles from the initial search, 27 (4.1%) met our inclusion criteria. In total, 37% (10/27) were commentaries, and 63% (17/27) were peer-reviewed empirical studies (11/27, 41% quantitative; 5/27, 19% qualitative; 1/27, 4% mixed methods; 1/27, 4% systematic reviews; and 1/27, 4% narrative reviews). Empirical studies were mostly small, rapidly conducted, and briefly reported. Most studies (25/27, 93%) identified marked digital disparities but lacked a strong theoretical lens. Proposed solutions focused on identifying and removing barriers, but the authors generally overlooked the pervasive impact of multiple layers of disadvantage. The data set included no theoretically informed studies that examined how different dimensions of disadvantage combined to affect digital health disparities. In our subsequent search, we identified 3 theoretical approaches that might help account for these digital disparities. Fundamental cause theory by Link and Phelan addresses why the association between socioeconomic status and health is pervasive and persists over time. Digital capital theory by Ragnedda and Ruiu explains how people mobilize resources to participate in digitally mediated activities and services. Intersectionality theory by Crenshaw states that systems of oppression are inherently bound together, creating singular social experiences for people who bear the force of multiple adverse social structures. A limitation of our initial sample was the sparse and undertheorized nature of the primary literature. The lack of attention to how digital health disparities emerge and play out both within and across categories of disadvantage means that solutions proposed to date may be oversimplistic and insufficient. Theories of multiple disadvantage have bearing on digital health, and there may be others of relevance besides those discussed in this paper. We call for greater interdisciplinary dialogue between theoretical research on multiple disadvantage and empirical studies on digital health disparities.

Advancements in artificial intelligence (AI) have driven extensive research into developing diverse multimodal data analysis approaches for smart healthcare. There is a scarcity of large-scale analysis of literature in this field based on quantitative approaches. This study performed a bibliometric and topic modeling examination on 683 articles from 2002 to 2022, focusing on research topics and trends, journals, countries/regions, institutions, authors, and scientific collaborations. Results showed that, firstly, the number of articles has grown from 1 in 2002 to 220 in 2022, with a majority being published in interdisciplinary journals that link healthcare and medical research and information technology and AI. Secondly, the significant rise in the quantity of research articles can be attributed to the increasing contribution of scholars from non-English speaking countries/regions and the noteworthy contributions made by authors in the USA and India. Thirdly, researchers show a high interest in diverse research issues, especially, cross-modality magnetic resonance imaging (MRI) for brain tumor analysis, cancer prognosis through multi-dimensional data analysis, and AI-assisted diagnostics and personalization in healthcare, with each topic experiencing a significant increase in research interest. There is an emerging trend towards issues such as applying generative adversarial networks and contrastive learning for multimodal medical image fusion and synthesis and utilizing the combined spatiotemporal resolution of functional MRI and electroencephalogram in a data-centric manner. This study is valuable in enhancing researchers’ and practitioners’ understanding of the present focal points and upcoming trajectories in AI-powered smart healthcare based on multimodal data analysis.

In recent years, the number of International Schools around the world has increased rapidly largely as a result of growth of new forms of International Schools, which differ markedly from the traditional forms. These new forms: are often operated on a for-profit commercial basis; are usually for children from the local (indigenous), wealthy population; and have been defined as International Schools because they are located in a non-English speaking country and English is the school's medium of communication. The growth of International Schools of the non-traditional type raises issues about the legitimacy of such schools. These new forms of International School face particular challenges in establishing themselves legitimately as 'international'. In this article, we develop a framework which is grounded in institutional theory to analyse the institutionalisation of and the consequent legitimacy of International Schools. We use the three pillars of institutionalisation which, by means of carriers, underpin the institutionalisation of organisations. We employ this framework to analyse and illustrate the legitimacy of a school's claim to be an International School and also to bring to light the challenges that schools face in establishing a legitimate claim to be 'international'.