Multilingual education: medical interns perceptions regarding the usefulness of non-mother tongue communications skills taught during the undergraduate curriculum.

BACKGROUND: This paper investigates the perceptions of medical interns regarding the usefulness of non-mother tongue communication skills taught during the undergraduate curriculum at the University of Cape Town in South Africa. In 2003, the university decided to incorporate Afrikaans and IsiXhosa communication skills into the new MBChB curriculum in order to meet the Faculty of Health Sciences goals to promote quality and equity in healthcare, and to prepare graduating health practitioners for multilingual communities where they would be serving. Despite annual internal evaluations and reviews of the languages courses, the usefulness, if any, of the additional languages in the working clinical environment had not been determined. METHODS: Data were collected during the second year of medical internship across a five-year period through survey questionnaires, as well as focus group interviews conducted in the Western Cape, South Africa. Surveys were conducted from 2009 to 2013. RESULTS: The study shows that the usefulness of each of the probed categories was not consistent across both languages. The interns expressed a need for an overall improvement of the isiXhosa course offering, while the outcomes for the Afrikaans language were more positive across all categories except for cultural understanding. CONCLUSION: The study indicates a positive trend amongst the interns towards developing usefulness in communication skills in Afrikaans and isiXhosa to communicate with their patients.

Automatic Spontaneous Speech Analysis for the Detection of Cognitive Functional Decline in Older Adults: Multilanguage Cross-Sectional Study.

BACKGROUND: The rise in life expectancy is associated with an increase in long-term and gradual cognitive decline. Treatment effectiveness is enhanced at the early stage of the disease. Therefore, there is a need to find low-cost and ecological solutions for mass screening of community-dwelling older adults. OBJECTIVE: This work aims to exploit automatic analysis of free speech to identify signs of cognitive function decline. METHODS: A sample of 266 participants older than 65 years were recruited in Italy and Spain and were divided into 3 groups according to their Mini-Mental Status Examination (MMSE) scores. People were asked to tell a story and describe a picture, and voice recordings were used to extract high-level features on different time scales automatically. Based on these features, machine learning algorithms were trained to solve binary and multiclass classification problems by using both mono- and cross-lingual approaches. The algorithms were enriched using Shapley Additive Explanations for model explainability. RESULTS: In the Italian data set, healthy participants (MMSE score≥27) were automatically discriminated from participants with mildly impaired cognitive function (20≤MMSE score≤26) and from those with moderate to severe impairment of cognitive function (11≤MMSE score≤19) with accuracy of 80% and 86%, respectively. Slightly lower performance was achieved in the Spanish and multilanguage data sets. CONCLUSIONS: This work proposes a transparent and unobtrusive assessment method, which might be included in a mobile app for large-scale monitoring of cognitive functionality in older adults. Voice is confirmed to be an important biomarker of cognitive decline due to its noninvasive and easily accessible nature.

BGLM: big data-guided LOINC mapping with multi-language support.

Motivation: Mapping internal, locally used lab test codes to standardized logical observation identifiers names and codes (LOINC) terminology has become an essential step in harmonizing electronic health record (EHR) data across different institutions. However, most existing LOINC code mappers are based on text-mining technology and do not provide robust multi-language support. Materials and methods: We introduce a simple, yet effective tool called big data-guided LOINC code mapper (BGLM), which leverages the large amount of patient data stored in EHR systems to perform LOINC coding mapping. Distinguishing from existing methods, BGLM conducts mapping based on distributional similarity. Results: We validated the performance of BGLM with real-world datasets and showed that high mapping precision could be achieved under proper false discovery rate control. In addition, we showed that the mapping results of BGLM could be used to boost the performance of Regenstrief LOINC Mapping Assistant (RELMA), one of the most widely used LOINC code mappers. Conclusions: BGLM paves a new way for LOINC code mapping and therefore could be applied to EHR systems without the restriction of languages. BGLM is freely available at https://github.com/Bin-Chen-Lab/BGLM.

Communication about distress and well-being: Epistemic and ethical considerations.

Communication about well-being and distress involves multiple stakeholders, including experts by experience (EBE), researchers, clinical practitioners, interpreters, and translators. Communication can involve a variety of discourses and languages and each of the stakeholders may employ diverging epistemologies to understand and explain experiences. These epistemologies may link to different sources of authority and be articulated using particular linguistic resources. Epistemic injustice can occur when stakeholders, intentionally or unintentionally, fail to recognise the validity of other stakeholders' ways of conceptualising and verbalising their experience of well-being and distress. Language lies at the heart of the risk of epistemic injustice involved in the process of expressing well-being and distress as seen in: 1) the interface between divergent discourses on well-being and distress (e.g., biomedical vs. spiritual); and 2) communications involving multiple linguistic resources, which can be subdivided into multi-language communications involving a) translation of assessment measures, and b) interpreted interactions. Some of the challenges of multi-language communication can be addressed by translators or interpreters who strive for conceptual equivalence. We argue, however, that all stakeholders have an important role as "epistemic brokers" in the languaging of possible epistemological differences. Effective epistemic brokering requires that all stakeholders are reflexively and critically aware of the risks of epistemic injustice inherent in multi-language communication. The article concludes with a set of prompts to help raise stakeholder awareness and reflexivity when engaging in communication about well-being and distress.

Burden of venous thromboembolism in patients with pancreatic cancer.

Pancreatic cancer (PC) is a devastating malignancy with fewer than 10% of patients being alive at 5 years after diagnosis. Venous thromboembolism (VTE) occurs in approximatively 20% of patients with PC, resulting in increased morbidity, mortality and significant health care costs. The management of VTE is particularly challenging in these frail patients. Adequate selection of the most appropriate anticoagulant for each individual patient according to the current international guidelines is warranted for overcoming treatment challenges. The International Initiative on Thrombosis and Cancer multi-language web-based mobile application (downloadable for free at www.itaccme.com) has been developed to help clinicians in decision making in the most complex situations. In this narrative review, we will discuss the contemporary epidemiology and burden of VTE in PC patients, the performances and limitations of current risk assessment models to predict the risk of VTE, as well as evidence from recent clinical trials for the primary prophylaxis and treatment of cancer-associated VTE that support up-dated clinical practice guidelines.

Mode displaying mouse cursors for reducing input language mode confusion: Utility and user attitude evaluation.

Users frequently commit typing errors due to input language mode confusion (ILMC) when switching between multiple languages. This study evaluated two mode display cursors (MDCs) as a potential solution to ILMC: the monochrome and color-changing MDCs. Two experiments were conducted to evaluate the two MDCs in different dimensions of usability. Experiment 1 evaluated the effects of MDCs on ILMC and related typing errors and Experiment 2, on self-reported preference, acceptance and annoyance. In Experiment 1, 45 participants were divided into three groups, that each performed multi-language typing using an ordinary mouse cursor and the two MDCs. The color-changing MDC was found to significantly reduce ILMC and related typing errors compared to the ordinary mouse cursor (p < .001). In Experiment 2, 30 participants performed three typical computer tasks using both MDCs. The mean annoyance rating was significantly larger for the color-changing MDC than for the monochrome MDC (p = .037).

Technology Enabled Clinical Care (TECC): Protocol for a Prospective Longitudinal Cohort Study of Smartphone-Augmented Mental Health Treatment.

BACKGROUND: Even before COVID-19, there has been an urgent need to expand access to and quality of mental health care. This paper introduces an 8-week treatment protocol to realize that vision-Technology Enabled Clinical Care (TECC). TECC offers innovation in clinical assessment, monitoring, and interventions for mental health. TECC uses the mindLAMP app to enable digital phenotyping, clinical communication, and smartphone-based exercises that will augment in-person or telehealth virtual visits. TECC exposes participants to an array of evidence-based treatments (cognitive behavioral therapy, dialectical behavior therapy, acceptance and commitment therapy) introduced through clinical sessions and then practiced through interactive activities provided through a smartphone app called mindLAMP. OBJECTIVE: TECC will test the feasibility of providing technology-enabled mental health care within an outpatient clinic; explore the practicality for providing this care to individuals with limited English proficiency; and track anxiety, depression, and mood symptoms for participants to measure the effectiveness of the TECC design. METHODS: The TECC study will assess the acceptability and efficacy of this care model in 50 participants as compared to an age- and gender-matched cohort of patients presenting with similar clinical severity of depression, anxiety, or psychotic symptoms. Participants will be recruited from clinics in the Metro Boston area. Aspects of TECC will be conducted in both Spanish and English to ensure wide access to care for multiple populations. RESULTS: The results of the TECC study will be used to support or adapt this model of care and create training resources to ensure its dissemination. The study results will be posted on ClinicalTrials.gov, with primary outcomes related to changes in mood, anxiety, and stress, and secondary outcomes related to engagement, alliance, and satisfaction. CONCLUSIONS: TECC combines new digital mental health technology with updated clinical protocols and workflows designed to ensure patients can benefit from innovation in digital mental health. Supporting multiple languages, TECC is designed to ensure digital health equity and highlights how mobile health can bridge, not expand, gaps in care for underserved populations. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/23771.

The development of the Compulsive Sexual Behavior Disorder Scale (CSBD-19): An ICD-11 based screening measure across three languages.

BACKGROUND: Compulsive Sexual Behavior Disorder (CSBD) is included in the eleventh edition of The International Classification of Diseases (ICD-11) as an impulse-control disorder. AIMS: The aim of the present work was to develop a scale (Compulsive Sexual Behavior Disorder Scale-CSBD-19) that can reliably and validly assess CSBD based on ICD-11 diagnostic guidelines. METHOD: Four independent samples of 9,325 individuals completed self-reported measures from three countries (the United States, Hungary, and Germany). The psychometric properties of the CSBD-19 were examined in terms of factor structure, reliability, measurement invariance, and theoretically relevant correlates. A potential threshold was determined to identify individuals with an elevated risk of CSBD. RESULTS: The five-factor model of the CSBD-19 (i.e., control, salience, relapse, dissatisfaction, and negative consequences) had an excellent fit to the data and demonstrated appropriate associations with the correlates. Measurement invariance suggested that the CSBD-19 functions similarly across languages. Men had higher means than women. A score of 50 points was found as an optimal threshold to identify individuals at high-risk of CSBD. CONCLUSIONS: The CSBD-19 is a short, valid, and reliable measure of potential CSBD based on ICD-11 diagnostic guidelines. Its use in large-scale, cross-cultural studies may promote the identification and understanding of individuals with a high risk of CSBD.

Utilizing a Digital Multi-Language Patient Questionnaire for Diagnostic Imaging Examinations.

In diagnostic imaging (DI) practice, patient questionnaires allow clinical staff to gather medical history information directly from patients. However, language barriers can prevent patients from completing the questionnaires and may endanger patient safety if the patient fails to indicate critical medical information. Interpreters are commonly employed to help patients convey important medical details; however, there are limits to their practical utilization. Thus, the purpose of this study was to evaluate the feasibility and practicality of a digital multi-language questionnaire designed to help overcome the language barriers between patients and clinical staff. The standard English-language questionnaire for bone mineral density (BMD) examinations was used in this study. It was translated into several languages and presented in an electronic form to patients in a language most suitable for them. The completed questionnaires, along with the patient responses, were automatically converted into English, allowing them to be reviewed by DI staff through a radiological information system (RIS) and picture archiving and communication system (PACS). Patients and clinical staff commented on the comfort of using the translated questionnaires. The modified Wald method was used to establish the confidence interval. The results showed that all patients and clinical staff were comfortable using the translated questionnaires. Ultimately, in this study we have developed a digital multi-language questionnaire for BMD examinations which can be converted into different languages and be stored in RIS and PACS. To the best of our knowledge, this approach had not been applied or tested elsewhere.

Outcome prediction for Bonebridge candidates based on audiological indication criteria.

OBJECTIVE: To re-evaluate current indication criteria and to estimate the audiological outcomes of patients with Bonebridge bone conduction implants based on preoperative bone conduction thresholds. METHODS: We assessed the outcome of 28 subjects with either conductive or mixed hearing loss (CMHL) or single-sided deafness (SSD) who were undergoing a Bonebridge implantation. We used linear regression to evaluate the influence of preoperative bone conduction thresholds of the better/poorer ear, indication group, and language (German- and French-speaking patients) on aided sound field thresholds. In addition, aided word recognition scores at 65dB sound pressure level were fit with a logistic model that included preoperative bone conduction thresholds of the better/poorer ear, indication group, and language as effects. RESULTS: We found that both aided sound field thresholds and word recognition were correlated with the preoperative bone conduction thresholds of the better hearing ear. No correlation between audiological outcomes and the preoperative bone conduction thresholds of the poorer ear, language, or indication group was found. CONCLUSION: Bone conduction thresholds of the better hearing ear should be used to estimate the outcome of patients undergoing Bonebridge implantation. We suggest the indication criteria for Bonebridge candidates considering maximal bone conduction thresholds of the better ear at 38dB HL to achieve an aided sound field threshold of at least 30dB hearing level and an aided word recognition score of at least 75% for monosyllabic words.