Language and Health最新文献

Stroke survivors (SSs) often experience cognitive decline following their initial stroke, necessitating repeat post-stroke cognitive assessments. Current methods of assessment, such as the pen-and-paper-based Montreal Cognitive Assessment (MoCA), is time-consuming and often reliant on seeing skilled clinicians in person. This is at a time when patients have a lot of often diverse rehabilitation needs. To address these challenges, our paper introduces the first system of its kind to be used for this cohort. CognoSpeak is an automated cognitive assessment system that people can use initially on the ward immediately post-stroke (baseline) and subsequently at home (follow-ups). CognoSpeak assesses cognitive decline by asking users to engage with a virtual agent by answering questions and completing clinically-motivated tasks and cognitive tests. The system then uses AI to extract and process speech, language, and interactional cues for cognitive decline. The system was originally developed for dementia; here, we show that it can successfully predict MoCA scores (regression) and identify cognitive decline predicated on a MoCA-based threshold (classification) in the stroke survivor cohort. We explore an extensive set of acoustic- and text-based features as well as different machine learning models. Leveraging a unique dataset of 55 SS CognoSpeak interactions, our findings show excellent performance for both regression and classification style prediction with the best regression result (Normalised Root Mean Squared Error (N-RMSE)) of 0.092. In addition, we show that direct classification of the MoCA score cutoff of 26 yields an F1-score of 0.74 (Specificity: 0.73, Sensitivity: 0.75) using a Logistic Regression Classifier. This demonstrates the first evidence of the system’s robustness and clinical potential.

Although Attention Deficit Hyperactivity Disorder (ADHD) is among the most common diagnoses in childhood, a formal diagnosis, frequently, is delayed until adulthood. As a result, the individuals who are not diagnosed in childhood miss out on the early treatment and may experience considerable social and pragmatic challenges, culminating in factors that impact their daily living, educational achievements and professional performance. Children and adolescents who do not receive an ADHD treatment carry their symptoms into adulthood, that typically result in functional and pragmatical difficulties. However, assessing pragmatic deficits in adults with ADHD presents challenges, stemming from various factors such as educational backgrounds, under-resourced family environments, compensatory mechanisms in individuals with high intelligence and the presence of other comorbid conditions. Consequently, overlooking pragmatic and functional difficulties can lead to significant social difficulties, which in turn may negatively impact their daily living, educational achievements and career progression. This study proposes a comprehensive and cost-effective approach to evaluating pragmatic skills in adults with ADHD, by adapting a systematic and standardized method, for the assessment of the pragmatic abilities, originally developed for neurotypical individuals by Acara and Bambini (2016). The results show the importance of incorporating this assessment tool into the diagnostic procedures for ADHD that can be further applied in the intervention programs. This assessment tool provides a valid onset criterion for advancing effective intervention programs that are focused on the pragmatic skills. Thus, this evaluation tool, first, can pinpoint pragmatic deficits within the ADHD community, and, second, can foster the development of the targeted intervention programs concentrated on enhancing pragmatic skills in the individuals with ADHD.

Natural Language Processing (NLP) technology has the potential to provide a non-invasive, cost-effective method using a timely intervention for detecting early-stage language and cognitive decline in individuals concerned about their memory. The proposed pre-screening language and cognition assessment model (PST-LCAM) is based on the functional linguistic model Role and Reference Grammar (RRG) to analyse and represent the structure and meaning of utterances, via a set of language production and cognition parameters. The model is trained on a DementiaBank dataset with markers of cognitive decline aligned to the global deterioration scale (GDS). A hybrid approach of qualitative linguistic analysis and assessment is applied, which includes the mapping of participants´ tasks of speech utterances and words to RRG phenomena. It uses a metric-based scoring with resulting quantitative scores and qualitative indicators as pre-screening results. This model is to be deployed in a user-centred conversational assessment platform.

This paper examined the attentiveness demonstrated by doctors to e-patients during online medical consultations (OMCs). Drawing upon data retrieved from www.chunyuyisheng.com (Chunyu Doctor), this study attempts to explore how doctors display attentiveness to e-patients and how attentiveness contributes to patient-centeredness during OMCs in China. It was found that three strategies (reformulation, mitigation, and empathy) were deployed by doctors to demonstrate attentiveness to e-patients during OMCs. Moreover, these three attentiveness-constructing strategies reveal the efforts of doctors toward patient-centeredness regarding communicative gaps in information, solidarity, and pathos. Notably, this paper discussed doctors’ demonstration of attentiveness as a joint goal-oriented activity, with the common goal of solving problems shared by doctors and e-patients. The findings above not only problematize the endemic idea that attentiveness is an intrapsychic essence from an interpersonal pragmatic perspective but also extend the line of doctor-patient communication by highlighting OMCs as a joint goal-oriented activity.

Living under the far-reaching ramifications of the Covid-19 pandemic, effective communication has been the order of the day in recent years. The very nature of the pandemic strikes home the crucial need to communicate multilingually in our increasingly (super)diverse world, in which translation has a big part to play. Constituting a socially shaped and socially shaping discourse, the multilingual communication and translation practices on the ground tell fascinating stories about a city’s demographic profile and multilingual repertoire during a public health crisis. So far, while a limited number of LL studies have been conducted in a few individual cities, there has been a glaring lack of scholarly engagement with Covid-related linguistic landscapes in our world’s global cities from a comparative perspective. To address this gap, framed within the broader context of crisis communication, this sociolinguistic study compares the Covidscapes between Dubai, Kuala Lumpur and Hong Kong, three dynamic Asian metropolises and commercial hubs featuring speakers of different languages. The signs in the three cities’ Covid-scapes all share similar themes (e.g. mask wearing and social distancing), represent multimodal and semiotic assemblages, and are realised in the form of top-down and bottom-up signage. However, the Covid-scape in Kuala Lumpur tends to involve mostly Malay and/or English and the Covid-scape in the superdiverse Dubai tends to be predominantly bilingual in Arabic and English only. In comparison, Hong Kong tends to mobilise a wider range of linguistic repertoire where multiple ethnic languages such as Hindi, Urdu, Nepali, Tagalog and Indonesian are involved (especially top-down officially instituted signs). This is fascinating (and counterintuitive) considering Dubai and Kuala Lumpur are significantly more ethnolinguistically diverse compared with Hong Kong, which features an ethnic Chinese majority. Using authentic real-world examples, the observed features and trends are discussed and analysed. The tentative reasons and implications of the findings are also explored.

Recent health communication studies have begun to look at online illness narratives, showing how narratives are used to report patients’ experience or to offer medical advice in various online contexts. However, few studies have sought to explore the communicative features of these online narratives in the Chinese context. Given the insufficient and uneven distribution of mental health resources and the intense stigma attached, an increasing number of Chinese patients with mental disorders are turning to online support groups (OSGs) for advice. We have limited understanding of Chinese patients’ lived experience or the potential of online illness narratives to be interpersonal tools for sharing advice. Drawing on computer-mediated discourse analysis, this study scrutinises narrative passages from a Chinese OSG to illustrate how individuals with mental illness interact in an online advisory context. The detailed analysis of narrative functions unpacks the potential of OSGs to provide storytelling opportunities for Chinese patients with mental disorders, allowing them to voice their concerns and experiences within the peer-to-peer network of relational understanding and support. This study also identifies a distinct feature of narrative activities in this online advisory context – the illness blog – and illustrates how its occurrence is related to the Chinese sociocultural values. This study can help raise awareness of illness narratives as a communication tool and facilitate culturally sensitive reactions of healthcare professionals towards patients’ narratives.

Research shows that the COVID-19 outbreak negatively affected people’s mental health with depression cases being the most prevalently reported mental disorder around the world. This motivated studies on the symptoms of depression through social media such as Twitter, with most of them focusing on behavioural changes in depressive individuals. Linguistic changes in tweets of depressed Twitter users however are under-researched. To date, research on linguistic markers of depression has been linked to self-focused attention and negativity bias in depressed individuals while other domains of cognitive theories of depression have remained relatively unexplored in linguistic studies. This gap in the literature is the motivation for the current paper on linguistic markers of depression in tweets during the pandemic. It focuses on sensitive markers of depression namely first-person singular pronouns, negative emotion words, and absolutist words as they reflect increased self-focus, negativity, and absolutist thinking in depressed individuals. The current study analyses the change in the use of these linguistic markers among depressed Twitter users based on tweets in English one year prior to and a year into COVID-19 pandemic. It also explores emerging linguistic markers of depression beyond the scope of self-focused attention, negativity bias, and absolutist thinking providing understanding of how depression manifests in language during global crises such as the pandemic.

Language and health studies is scientific, pioneering and promising in nature given the close yet intricate relationship between human’s language and health. A diverse range of research topics encompasses the panorama of language and health studies, with the overarching objective of promoting the holistic well-being of individuals across the entire spectrum of age demographics, spanning from children, through adults, to the elderly. The present systematic review corroborates a flourishing trajectory of language and health research over the past three decades. Language disorders and speech-language pathology are among the most critical research topics in the field, with a primary focus on diagnosis and intervention. There are also rich investigations of language and mental health disorders in atypical populations. Clinical analysis, applied conversation analysis and narrative medicine are the three important approaches to the examination of communication in medical and healthcare interactions, which is crucial to public health promotion. The application of cutting-edge technologies and interdisciplinary cooperation can provide innovative solutions to the difficulties and challenges that arise in this field.

This article provides readers with an overview of a population of clients that requires special consideration in healthcare settings: children and adults with communication disorders. In addition to standard barriers to effective communication between patients and doctors, people with communication disorders face a further challenge – communicating with medical and health professionals when their speech and language skills are impaired. The article examines how communication skills may fail to develop normally in the early years or may break down in adulthood and later life in the context of illness, injury or disease. Several communication disorders are illustrated using a lifespan perspective. The prevalence and impact of communication disorders are also considered. Finally, the article examines how communication disorders are assessed and treated by speech-language pathologists. The discussion serves as a primer or orientation for health practitioners and communication researchers to an important population of clients who have largely been neglected in health communication research that has been conducted to date.

Unanticipated difficult intubation is a relatively common problem anaesthetists face in everyday practice. Algorithms to manage the problem were issued (Japanese Society of Anesthesiologists, 2014), but how anaesthetists actually perceive the problem and respond to the difficulties with other healthcare professionals present is still to be uncovered. Drawing on the concept of resilient healthcare (Hollnagel et al., 2013), which values “how things go well”, this study analysed interactions in simulated emergencies between a less experienced anaesthetist (trainee) and an experienced anaesthetist (trainer). The latter took a role as a nurse and led the scenario of difficult intubation. Five sessions with the same trainer, one of five different trainees and a manikin as a patient were recorded with a 360-degree camera in an operating room at a large teaching hospital in Japan. The data was transcribed and analysed with discourse and multimodal corpus analytic approaches. In the simulated interactions, four phases of grounding (Clark, 1996) were observed in the joint decision-making process between the trainer and the trainee: (1) the trainer’s information presentation with her gaze address at the referent, (2) the trainee’s gaze following and acknowledgement of information reception, (3) the trainer’s prompt for the trainee’s decision-making, and (4) the trainee’s (or trainer’s) giving instruction to manage the difficulty. The trainer presented the patient’s condition and visual/audio information affordable in the environment (e.g., signals on a vital monitor), using verbal and multimodal resources, i.e., gaze address and deictic gestures. The participants as individual sensory agencies were engaged in the embodied process of shared sense-making in the particular context to establish common ground for joint decision-making on immediate actions required.