Language and Health最新文献

This paper investigates the experiences of patients in communicating with healthcare practitioners within the context of supported self-management in the UK. Employing an innovative analytical concept of “narrative modulation”, this study examines narrative data from patients’ focus group discussions. Two contrasting processes, attunement and misattunement, emerge as narrative modulators that shape and form the meaning and trajectory of participants’ storytelling. The study identifies multiple instances of misattunement in patient-practitioner interactions, highlighting a prevailing emphasis on diagnosis and treatment-focused perspectives, often at the expense of individual patients' experiences during clinical encounters. Despite these challenges, the participants expressed a desire for care that listens to and understands their unique experiences. They also wished to play an active role in their healthcare decisions, endorsing attunement, which promotes understanding and collaborative self-management supported by practitioners. This paper further discusses the implications of these findings for improving both patient-practitioner communication and supported self-management.

As the emergency phase of the COVID-19 pandemic subsides, the long-term health problems caused by SARS-CoV-2 infection are becoming increasingly clear. So-called Long COVID, or post COVID-19 condition, is a debilitating illness that impacts functioning for months and even years after infection. Alongside physical symptoms, Long COVID has a particularly insidious effect on cognition and language. While many studies have documented non-linguistic cognitive impairments in people with Long COVID, what has not been documented to any significant extent is the presence and duration of language difficulties in Long COVID. This study addresses this lack of research by examining the cognitive-linguistic skills of 41 adults with Long COVID. These adults were assessed at two time points using a test protocol of 12 language tasks. This paper describes the findings of the 6-month follow-up study. Results indicate that difficulties in immediate and delayed verbal recall persist long after the onset of COVID symptoms, even as improvements occur in verbal fluency and the informativeness of spoken discourse. It is argued that these difficulties are a significant contributing factor in a lack of work return in these adults. Implications of these findings for the provision of speech-language pathology services to these adults and occupational health policies relating to Long COVID are discussed.

Endometriosis is a chronic gynecological illness faced by an estimated one-tenth of women worldwide. Despite being a common condition, studies of the disease in Latin American settings are still scarce. This paper presents a study of 30 autobiographical interviews with Chilean patients who are L1 Spanish speakers. Our study aims to fill the gap in understanding the endometriosis experience of Latin American women, unveiling how to assist the patients better and improve their quality of life. It is one of the first studies to describe the experience of Chilean women in navigating the disease and the impacts on their routines. We used a mixed-methods approach to achieve our goal, employing a combination of NLP and content analysis. First, we generated word embeddings for three main keywords, "pain," "endometriosis," and "menstruation." Furthermore, we processed the data to locate occurrences of "pain" in the corpus. We coded the occurrences into nine semantic domains of the endometriosis pain experience: intensity, normalization, treatment, frequency, menstruation, feeling, pain location, symptom, and impact. Our results shed light on the details of the journey with endometriosis and may lead to improvements in patient-doctor communication and policymaking to benefit patients.

Utilizing the Putonghua Communicative Development Inventory-Toddler Form, this longitudinal study assessed expressive language development (including lexicon, grammar, and decontextualized language) twice over a year’s span in two subgroups (high verbal, low verbal) of 77 2–6-year-old Mandarin-exposed children with autism spectrum disorder (ASD). Both subgroups showed the steeper increase of structural language (lexicon and grammar) vs. the flatter growth of decontextualized language. Moreover, children’s initial language skills (but not autism severity or language environment) predicted language outcomes one year later in both groups. The use of decontextualized language also predicted structural language development in the low verbal group. These findings confirmed the uneven expressive language growth across multiple language domains in subgroups of children with ASD and underscored the contribution of early language skills to their expressive language development. Moreover, the slow growth and significant predictivity of decontextualized language warrant targeted intervention in promoting children with ASD’s talk beyond the ‘here-and-now’ situation in communication.

This article discusses insights from a research on the management of emotions in medical interactions involving Italian healthcare providers, Arabic speaking interpreters and Arabic speaking patients. The findings suggest that the possibility for patient’s emotions to become relevant in the medical encounter is affected by the activity of interpreters as mediators of the inter-linguistic interaction. While this contribution also considers examples of interpreters’ choices excluding the emotions of the patients from the interaction, the discussion focuses on affective formulations of patient’s expression of emotions, as an interactional resource to make doctors aware of patients’ emotional expressions emerged from dyadic monolingual interactions. This article concludes by suggesting that interpreters as linguistic mediators may effectively promote emotional literacy in healthcare interactions, promoting a patient-centred model of multilingual healthcare.

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.