scholarly journals Evaluation of a Language Translation App in an Undergraduate Medical Communication Course: Proof-of-Concept and Usability Study

10.2196/31559 ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. e31559
Author(s):  
Anne Herrmann-Werner ◽  
Teresa Loda ◽  
Stephan Zipfel ◽  
Martin Holderried ◽  
Friederike Holderried ◽  
...  
Keyword(s):  
Health Care ◽  
Health Care Professionals ◽  
Gold Standard ◽  
Language Translation ◽  
Language Barriers ◽  
Free Text ◽  
Practical Training ◽  
Proof Of Concept ◽  
Medical Communication ◽  
Teaching Unit

Background Language barriers in medical encounters pose risks for interactions with patients, their care, and their outcomes. Because human translators, the gold standard for mitigating language barriers, can be cost- and time-intensive, mechanical alternatives such as language translation apps (LTA) have gained in popularity. However, adequate training for physicians in using LTAs remains elusive. Objective A proof-of-concept pilot study was designed to evaluate the use of a speech-to-speech LTA in a specific simulated physician-patient situation, particularly its perceived usability, helpfulness, and meaningfulness, and to assess the teaching unit overall. Methods Students engaged in a 90-min simulation with a standardized patient (SP) and the LTA iTranslate Converse. Thereafter, they rated the LTA with six items—helpful, intuitive, informative, accurate, recommendable, and applicable—on a 7-point Likert scale ranging from 1 (don’t agree at all) to 7 (completely agree) and could provide free-text responses for four items: general impression of the LTA, the LTA’s benefits, the LTA’s risks, and suggestions for improvement. Students also assessed the teaching unit on a 6-point scale from 1 (excellent) to 6 (insufficient). Data were evaluated quantitatively with mean (SD) values and qualitatively in thematic content analysis. Results Of 111 students in the course, 76 (68.5%) participated (59.2% women, age 20.7 years, SD 3.3 years). Values for the LTA’s being helpful (mean 3.45, SD 1.79), recommendable (mean 3.33, SD 1.65) and applicable (mean 3.57, SD 1.85) were centered around the average of 3.5. The items intuitive (mean 4.57, SD 1.74) and informative (mean 4.53, SD 1.95) were above average. The only below-average item concerned its accuracy (mean 2.38, SD 1.36). Students rated the teaching unit as being excellent (mean 1.2, SD 0.54) but wanted practical training with an SP plus a simulated human translator first. Free-text responses revealed several concerns about translation errors that could jeopardize diagnostic decisions. Students feared that patient-physician communication mediated by the LTA could decrease empathy and raised concerns regarding data protection and technical reliability. Nevertheless, they appreciated the LTA’s cost-effectiveness and usefulness as the best option when the gold standard is unavailable. They also reported wanting more medical-specific vocabulary and images to convey all information necessary for medical communication. Conclusions This study revealed the feasibility of using a speech-to-speech LTA in an undergraduate medical course. Although human translators remain the gold standard, LTAs could be valuable alternatives. Students appreciated the simulated teaching and recognized the LTA’s potential benefits and risks for use in real-world clinical settings. To optimize patients’ and health care professionals’ experiences with LTAs, future investigations should examine specific design options for training interventions and consider the legal aspects of human-machine interaction in health care settings.

scholarly journals Evaluation of a Language Translation App in an Undergraduate Medical Communication Course: Proof-of-Concept and Usability Study (Preprint)

2021 ◽  
Author(s):  
Anne Herrmann-Werner ◽  
Teresa Loda ◽  
Stephan Zipfel ◽  
Martin Holderried ◽  
Friederike Holderried ◽  
...  
Keyword(s):  
Health Care ◽  
Health Care Professionals ◽  
Gold Standard ◽  
Language Translation ◽  
Language Barriers ◽  
Free Text ◽  
Practical Training ◽  
Proof Of Concept ◽  
Medical Communication ◽  
Teaching Unit

BACKGROUND Language barriers in medical encounters pose risks for interactions with patients, their care, and their outcomes. Because human translators, the gold standard for mitigating language barriers, can be cost- and time-intensive, mechanical alternatives such as language translation apps (LTA) have gained in popularity. However, adequate training for physicians in using LTAs remains elusive. OBJECTIVE A proof-of-concept pilot study was designed to evaluate the use of a speech-to-speech LTA in a specific simulated physician-patient situation, particularly its perceived usability, helpfulness, and meaningfulness, and to assess the teaching unit overall. METHODS Students engaged in a 90-min simulation with a standardized patient (SP) and the LTA iTranslate Converse. Thereafter, they rated the LTA with six items—<i>helpful</i>, <i>intuitive</i>, <i>informative</i>, <i>accurate</i>, <i>recommendable</i>, and <i>applicable—</i>on a 7-point Likert scale ranging from 1 (<i>don’t agree at all</i>) to 7 (<i>completely agree</i>) and could provide free-text responses for four items: general impression of the LTA, the LTA’s benefits, the LTA’s risks, and suggestions for improvement. Students also assessed the teaching unit on a 6-point scale from 1 (<i>excellent</i>) to 6 (<i>insufficient</i>). Data were evaluated quantitatively with mean (SD) values and qualitatively in thematic content analysis. RESULTS Of 111 students in the course, 76 (68.5%) participated (59.2% women, age 20.7 years, SD 3.3 years). Values for the LTA’s being <i>helpful</i> (mean 3.45, SD 1.79), <i>recommendable</i> (mean 3.33, SD 1.65) and <i>applicable</i> (mean 3.57, SD 1.85) were centered around the average of 3.5. The items <i>intuitive</i> (mean 4.57, SD 1.74) and <i>informative</i> (mean 4.53, SD 1.95) were above average. The only below-average item concerned its <i>accuracy</i> (mean 2.38, SD 1.36). Students rated the teaching unit as being excellent (mean 1.2, SD 0.54) but wanted practical training with an SP plus a simulated human translator first. Free-text responses revealed several concerns about translation errors that could jeopardize diagnostic decisions. Students feared that patient-physician communication mediated by the LTA could decrease empathy and raised concerns regarding data protection and technical reliability. Nevertheless, they appreciated the LTA’s cost-effectiveness and usefulness as the best option when the gold standard is unavailable. They also reported wanting more medical-specific vocabulary and images to convey all information necessary for medical communication. CONCLUSIONS This study revealed the feasibility of using a speech-to-speech LTA in an undergraduate medical course. Although human translators remain the gold standard, LTAs could be valuable alternatives. Students appreciated the simulated teaching and recognized the LTA’s potential benefits and risks for use in real-world clinical settings. To optimize patients’ and health care professionals’ experiences with LTAs, future investigations should examine specific design options for training interventions and consider the legal aspects of human-machine interaction in health care settings.

scholarly journals Sentiment Analysis Techniques Applied to Raw-Text Data from a Csq-8 Questionnaire about Mindfulness in Times of COVID-19 to Improve Strategy Generation

2021 ◽  
Vol 18 (12) ◽  
pp. 6408
Author(s):  
Mario Jojoa Acosta ◽  
Gema Castillo-Sánchez ◽  
Begonya Garcia-Zapirain ◽  
Isabel de la Torre Díez ◽  
Manuel Franco-Martín
Keyword(s):  
Health Care ◽  
Natural Language Processing ◽  
Natural Language ◽  
Sentiment Analysis ◽  
Transfer Learning ◽  
Language Processing ◽  
Health Care Professionals ◽  
Ground Truth ◽  
Relevant Information ◽  
Free Text

The use of artificial intelligence in health care has grown quickly. In this sense, we present our work related to the application of Natural Language Processing techniques, as a tool to analyze the sentiment perception of users who answered two questions from the CSQ-8 questionnaires with raw Spanish free-text. Their responses are related to mindfulness, which is a novel technique used to control stress and anxiety caused by different factors in daily life. As such, we proposed an online course where this method was applied in order to improve the quality of life of health care professionals in COVID 19 pandemic times. We also carried out an evaluation of the satisfaction level of the participants involved, with a view to establishing strategies to improve future experiences. To automatically perform this task, we used Natural Language Processing (NLP) models such as swivel embedding, neural networks, and transfer learning, so as to classify the inputs into the following three categories: negative, neutral, and positive. Due to the limited amount of data available—86 registers for the first and 68 for the second—transfer learning techniques were required. The length of the text had no limit from the user’s standpoint, and our approach attained a maximum accuracy of 93.02% and 90.53%, respectively, based on ground truth labeled by three experts. Finally, we proposed a complementary analysis, using computer graphic text representation based on word frequency, to help researchers identify relevant information about the opinions with an objective approach to sentiment. The main conclusion drawn from this work is that the application of NLP techniques in small amounts of data using transfer learning is able to obtain enough accuracy in sentiment analysis and text classification stages.

scholarly journals Autoencoder as a New Method for Maintaining Data Privacy While Analyzing Videos of Patients With Motor Dysfunction: Proof-of-Concept Study

10.2196/16669 ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. e16669
Author(s):  
Marcus D'Souza ◽  
Caspar E P Van Munster ◽  
Jonas F Dorn ◽  
Alexis Dorier ◽  
Christian P Kamm ◽  
...  
Keyword(s):  
Health Care ◽  
Health Care Professionals ◽  
Data Privacy ◽  
Neurological Diseases ◽  
Weighted Kappa ◽  
Relevant Information ◽  
Machine Learning Algorithms ◽  
Motor Dysfunction ◽  
Proof Of Concept ◽  
Concept Study

Background In chronic neurological diseases, especially in multiple sclerosis (MS), clinical assessment of motor dysfunction is crucial to monitor the disease in patients. Traditional scales are not sensitive enough to detect slight changes. Video recordings of patient performance are more accurate and increase the reliability of severity ratings. When these recordings are automated, quantitative disability assessments by machine learning algorithms can be created. Creation of these algorithms involves non–health care professionals, which is a challenge for maintaining data privacy. However, autoencoders can address this issue. Objective The aim of this proof-of-concept study was to test whether coded frame vectors of autoencoders contain relevant information for analyzing videos of the motor performance of patients with MS. Methods In this study, 20 pre-rated videos of patients performing the finger-to-nose test were recorded. An autoencoder created encoded frame vectors from the original videos and decoded the videos again. The original and decoded videos were shown to 10 neurologists at an academic MS center in Basel, Switzerland. The neurologists tested whether the 200 videos were human-readable after decoding and rated the severity grade of each original and decoded video according to the Neurostatus-Expanded Disability Status Scale definitions of limb ataxia. Furthermore, the neurologists tested whether ratings were equivalent between the original and decoded videos. Results In total, 172 of 200 (86.0%) videos were of sufficient quality to be ratable. The intrarater agreement between the original and decoded videos was 0.317 (Cohen weighted kappa). The average difference in the ratings between the original and decoded videos was 0.26, in which the original videos were rated as more severe. The interrater agreement between the original videos was 0.459 and that between the decoded videos was 0.302. The agreement was higher when no deficits or very severe deficits were present. Conclusions The vast majority of videos (172/200, 86.0%) decoded by the autoencoder contained clinically relevant information and had fair intrarater agreement with the original videos. Autoencoders are a potential method for enabling the use of patient videos while preserving data privacy, especially when non–health-care professionals are involved.

scholarly journals Health Care Professionals’ Pain Narratives in Hospitalized Children’s Medical Records. Part 1: Pain Descriptors

2013 ◽  
Vol 18 (5) ◽  
pp. e75-e83 ◽  
Author(s):  
Judy Rashotte ◽  
Geraldine Coburn ◽  
Denise Harrison ◽  
Bonnie J Stevens ◽  
Janet Yamada ◽  
...  
Keyword(s):  
Health Care ◽  
Health Care Professionals ◽  
Medical Records ◽  
Written Language ◽  
Free Text ◽  
Hospitalized Children ◽  
Pediatric Hospitals ◽  
Qualitative Descriptive ◽  
Pain Descriptors ◽  
Children's Pain

BACKGROUND: Although documentation of children’s pain by health care professionals is frequently undertaken, few studies have explored the nature of the language used to describe pain in the medical records of hospitalized children.OBJECTIVES: To describe health care professionals’ use of written language related to the quality and quantity of pain experienced by hospitalized children.METHODS: Free-text pain narratives documented during a 24 h period were collected from the medical records of 3822 children (0 to 18 years of age) hospitalized on 32 inpatient units in eight Canadian pediatric hospitals. A qualitative descriptive exploration using a content analysis approach was used.RESULTS: Pain narratives were documented a total of 5390 times in 1518 of the 3822 children’s medical records (40%). Overall, word choices represented objective and subjective descriptors. Two major categories were identified, with their respective subcategories of word indicators and associated cues: indicators of pain, including behavioural (eg, vocal, motor, facial and activities cues), affective and physiological cues, and children’s descriptors; and word qualifiers, including intensity, comparator and temporal qualifiers.CONCLUSIONS: The richness and complexity of vocabulary used by clinicians to document children’s pain lend support to the concept that the word ‘pain’ is a label that represents a myriad of different experiences. There is potential to refine pediatric pain assessment measures to be inclusive of other cues used to identify children’s pain. The results enhance the discussion concerning the development of standardized nomenclature. Further research is warranted to determine whether there is congruence in interpretation across time, place and individuals.

scholarly journals Automated analysis of free-text comments and dashboard representations in patient experience surveys: a multimethod co-design study

2019 ◽  
Vol 7 (23) ◽  
pp. 1-160
Author(s):  
Carol Rivas ◽  
Daria Tkacz ◽  
Laurence Antao ◽  
Emmanouil Mentzakis ◽  
Margaret Gordon ◽  
...  
Keyword(s):  
Health Care ◽  
Patient Experience ◽  
Scoping Review ◽  
Health Care Professionals ◽  
Technology Development ◽  
Cost Benefit ◽  
Rapid Review ◽  
Free Text ◽  
Data Sets ◽  
Rule Based

BackgroundPatient experience surveys (PESs) often include informative free-text comments, but with no way of systematically, efficiently and usefully analysing and reporting these. The National Cancer Patient Experience Survey (CPES), used to model the approach reported here, generates > 70,000 free-text comments annually.Main aimTo improve the use and usefulness of PES free-text comments in driving health service changes that improve the patient experience.Secondary aims(1) To structure CPES free-text comments using rule-based information retrieval (IR) (‘text engineering’), drawing on health-care domain-specific gazetteers of terms, with in-built transferability to other surveys and conditions; (2) to display the results usefully for health-care professionals, in a digital toolkit dashboard display that drills down to the original free text; (3) to explore the usefulness of interdisciplinary mixed stakeholder co-design and consensus-forming approaches in technology development, ensuring that outputs have meaning for all; and (4) to explore the usefulness of Normalisation Process Theory (NPT) in structuring outputs for implementation and sustainability.DesignA scoping review, rapid review and surveys with stakeholders in health care (patients, carers, health-care providers, commissioners, policy-makers and charities) explored clinical dashboard design/patient experience themes. The findings informed the rules for the draft rule-based IR [developed using half of the 2013 Wales CPES (WCPES) data set] and prototype toolkit dashboards summarising PES data. These were refined following mixed stakeholder, concept-mapping workshops and interviews, which were structured to enable consensus-forming ‘co-design’ work. IR validation used the second half of the WCPES, with comparison against its manual analysis; transferability was tested using further health-care data sets. A discrete choice experiment (DCE) explored which toolkit features were preferred by health-care professionals, with a simple cost–benefit analysis. Structured walk-throughs with NHS managers in Wessex, London and Leeds explored usability and general implementation into practice.Key outcomesA taxonomy of ranked PES themes, a checklist of key features recommended for digital clinical toolkits, rule-based IR validation and transferability scores, usability, and goal-oriented, cost–benefit and marketability results. The secondary outputs were a survey, scoping and rapid review findings, and concordance and discordance between stakeholders and methods.Results(1) The surveys, rapid review and workshops showed that stakeholders differed in their understandings of the patient experience and priorities for change, but that they reached consensus on a shortlist of 19 themes; six were considered to be core; (2) the scoping review and one survey explored the clinical toolkit design, emphasising that such toolkits should be quick and easy to use, and embedded in workflows; the workshop discussions, the DCE and the walk-throughs confirmed this and foregrounded other features to form the toolkit design checklist; and (3) the rule-based IR, developed using noun and verb phrases and lookup gazetteers, was 86% accurate on the WCPES, but needs modification to improve this and to be accurate with other data sets. The DCE and the walk-through suggest that the toolkit would be well accepted, with a favourable cost–benefit ratio, if implemented into practice with appropriate infrastructure support.LimitationsSmall participant numbers and sampling bias across component studies. The scoping review studies mostly used top-down approaches and focused on professional dashboards. The rapid review of themes had limited scope, with no second reviewer. The IR needs further refinement, especially for transferability. New governance restrictions further limit immediate use.ConclusionsUsing a multidisciplinary, mixed stakeholder, use of co-design, proof of concept was shown for an automated display of patient experience free-text comments in a way that could drive health-care improvements in real time. The approach is easily modified for transferable application.Future workFurther exploration is needed of implementation into practice, transferable uses and technology development co-design approaches.FundingThe National Institute for Health Research Health Services and Delivery Research programme.

Perspective changes through transcultural mediation training: A qualitative study of trainees, instructors, and experts

2021 ◽  
pp. 136346152110629
Author(s):  
Anaïs Ogrizek ◽  
Marie Rose Moro ◽  
Serge Bouznah ◽  
Jonathan Lachal
Keyword(s):  
Health Care ◽  
Health Care Professionals ◽  
Interpretative Phenomenological Analysis ◽  
Role Playing ◽  
Practical Training ◽  
Subjective Experiences ◽  
Structured Interviews ◽  
Pedagogical Tools ◽  
Transmission Of Knowledge

To deal with cultural misunderstandings in health care due to increased migration, the Babel Centre—a training and mediation center—developed “transcultural mediation”: a service meant to help health-care professionals encountering difficulties with migrant patients and their families. One of the center's health-care professionals, trained as a mediator, and a cultural broker jointly conduct the mediation session. In 2017, the center initiated a specialized training program to teach health-care professionals the skills needed to serve as transcultural mediators. We conducted a study to evaluate, through the trainees’ and instructors’ subjective experiences, the quality of this innovative training. We used semi-structured interviews and focus groups to question seven trainees, three instructors, and three experts in transcultural psychology at different stages of the 10-month program (before, at midpoint, and afterwards). We used Interpretative Phenomenological Analysis to explore the data. The themes are organized around the central concept of the transmission of knowledge from instructors to trainees and vice versa. Trainees were globally satisfied with this program by its end but did not feel able to lead a mediation by then, due to insufficient anthropology knowledge and practical training. Training in transcultural mediation resembles that for resolving situational problems. It cannot be taught by an approach based on reasoning by the inverse problem method, used for teaching medical sciences. Pedagogical tools more suited to problem solving, such as role-playing or use of senior-assisted mediations, should be used to improve the quality of this training.

scholarly journals Health Care Professionals’ Pain Narratives in Hospitalized Children’S Medical Records. Part 2: Structure and Content

2013 ◽  
Vol 18 (5) ◽  
pp. e84-e93
Author(s):  
Judy Rashotte ◽  
Denise Harrison ◽  
Geraldine Coburn ◽  
Janet Yamada ◽  
Bonnie J Stevens ◽  
...  
Keyword(s):  
Health Care ◽  
Acute Pain ◽  
Health Care Professionals ◽  
Medical Records ◽  
Management Plan ◽  
Free Text ◽  
Pain Status ◽  
Pain Intervention ◽  
Qualitative Descriptive ◽  
Numerical Representations

BACKGROUND: Although clinical narratives – described as free-text notations – have been noted to be a source of patient information, no studies have examined the composition of pain narratives in hospitalized children’s medical records.OBJECTIVES: To describe the structure and content of health care professionals’ narratives related to hospitalized children’s acute pain.METHODS: All pain narratives documented during a 24 h period were collected from the medical records of 3822 children (0 to 18 years of age) hospitalized in 32 inpatient units in eight Canadian pediatric hospitals. A qualitative descriptive exploration using a content analysis approach was performed.RESULTS: Three major structural elements with their respective categories and subcategories were identified: information sources, including clinician, patient, parent, dual and unknown; compositional archetypes, including baseline pain status, intermittent pain updates, single events, pain summation and pain management plan; and content, including pain declaration, pain assessment, pain intervention and multidimensional elements of care.CONCLUSIONS: The present qualitative analysis revealed the multidimensionality of structure and content that was used to document hospitalized children’s acute pain. The findings have the potential to inform debate on whether the multidimensionality of pain narratives’ composition is a desirable feature of documentation and how narratives can be refined and improved. There is potential for further investigation into how health care professionals’ pain narratives could have a role in generating guidelines for best pain documentation practice beyond numerical representations of pain intensity.

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