Health Care Situations Research Articles

Enhancing Health Wellbeing of Chronic Patient Through Digital Health; A Systematic Review of Best Nursing Practices and Lessons Learned

Background: Context: Digital health interventions have become essential instruments in contemporary medicine, providing viable means of improving patient outcomes and healthcare provision. The goal of this study is to examine the impact, difficulties, and potential future directions of digital health interventions across a range of healthcare situations by synthesizing results from 12 carefully chosen studies. Aim: This study's objective is to thoroughly examine and summarize the body of research on digital health interventions, with an emphasis on acceptance and utilization as well as implementation and efficacy. Method: Twelve pertinent papers published between 2016 and 2024 were found after a thorough search of electronic databases. Numerous digital health interventions were covered by these research, such as remote monitoring systems, telemedicine, and mobile applications. In order to find common themes, sub-themes, and patterns among the chosen research, thematic analysis was used in the data synthesis process. Results: A number of important themes emerged from the thematic analysis, including interoperability problems, patient engagement, healthcare provider acceptability, regulatory concerns, and usability issues. The sub-themes that fell under these categories emphasized the variables that affect the uptake and efficacy of digital health interventions. Conclusion: The synthesis of data emphasizes how digital health initiatives can increase clinical results, improve patient care, and streamline the delivery of healthcare. But in order to fully reap the benefits, major obstacles like interoperability problems, regulatory difficulties, and usability impediments need to be solved. The recommendations put forth aim to promote innovation and evidence-based practice in digital health by stressing user-centered design, improving digital literacy among medical practitioners, and encouraging interdisciplinary collaboration.

The Intersection of Health Policy and Technology: Applying Quantum Computing for Optimizing Healthcare System Simulations and Predictions

The convergence of fitness coverage and generation is a vital frontier in present-day healthcare, giving probabilities for innovation and optimization that have no means to visible earlier. The cause of this paper is to research the capacity for quantum computing to enhance computer simulations and forecasts of healthcare systems. To revolutionise customized medication processes, provided a progressive approach that everybody termed Efficient Personalised Medicine through Quantum Machine Learning Analysis (EPM-QMLA). This approach combines the abilities of quantum computing with device learning. The significance of this work is living inside the fact that it has the potential to substantially beautify the results of healthcare by way of making it possible to expand remedy plans which are greater correct and individualized. Nevertheless, there are limitations, inclusive of the fact that quantum computing programs in healthcare are still in their infant degrees, which necessitates the introduction of stable infrastructure and algorithmic advancements. The modern capacity of EPM-QMLA is verified through simulated analyses in a lot of healthcare situations. This demonstrates the capability of EPM-QMLA to optimise useful resource allocation, predict infection progression, and personalize remedies to particular patient profiles. Through this examine, the promise of quantum computing as a sturdy device for advancing healthcare coverage and exercise is highlighted. This will pave the manner for a healthcare device this is greater efficient and targeted on the patient.

Reflections from Chinese and Japanese Physicians on Medical Disputes

Physician–patient disputes are a major problem in healthcare. Physician–patient conflicts, workplace violence, and direct involvement in disputes have a significant negative impact on the well-being of physicians. China and Japan have similar cultures but differing healthcare systems. The present study aimed to examine and compare the experiences and perceptions of Chinese and Japanese physicians regarding medical disputes. Qualitative descriptive content analysis was performed for 18 cases from each country to assess the major issues involved in each case and their impact on the physicians. Common issues in medical disputes for both countries included monetary motives of patients and/or families, violence/threats from patients and/or families, the inability of patients and/or families to understand the risk of complications, and the uncertainties of medicine. The serious impact of medical disputes on the mental health and professionalism of physicians was also an issue shared by physicians of both countries. There were, however, differences in the magnitude and frequency of these issues between the two countries. Pre-existing distrust of physicians among patients and/or families was noted only by Chinese physicians, and insufficient information disclosure by physicians was noted only by Japanese physicians. In conclusion, there were similarities and differences between the two countries in the perceptions of physicians regarding medical disputes. Our analysis revealed differing healthcare situations due to cultural and institutional differences as well as universal problems intrinsic to medicine. Based on our results, we propose several key principles to improve the physician–patient relationship.

Why are models for collaboration so confusing and difficult? Perceptions by health and social care professionals on developing and implementing models for collaboration

ABSTRACT Introduction Many situations in health and social care require collaboration to ensure seamless and good care with the person in focus. However, collaboration can be a difficult and confusing process. Hence, organizations often support it by developing and implementing models for collaboration. Aim This study aimed to explore health and social care professionals’ perceptions of collaboration models, as well as what difficulties they perceived in developing and implementing them in a municipality. Method Data was collected in a Swedish municipality, through mainly interviews with participating professionals and analysed using inductive content analysis. Results The professionals’ responses illustrated variations in perceptions of what constitutes a collaboration model (i.e. core values, a framework, a process, or a function) and why collaboration models are needed (i.e. for the good of the resident, for the good of the organization, or for the good of society). Furthermore, several perceived difficulties in developing and implementing collaboration models were captured. Conclusion The varied perceptions of collaboration models, together with the captured difficulties, help explain why models for collaboration are seen as confusing and difficult to develop and implement. This study can increase healthcare managements’ understanding of the complexity of collaboration models and assist future development and implementation.

User Personas for a "Better Design" of Nation-Wide EHRs Based on Thorough Expert Evaluation and Field Analysis: Modeling Users as Individuals Plus Family Members for an Enhanced Mapping of Healthcare Situations.

Electronic Health Records (EHRs) are pivotal in prevention, therapy, and care. Their design necessitates the representation of users, activities, context, and technology. Among various participative and ethnographic design methods, user personas are an effective tool for encapsulating users in the design process. Goals and methods: This research focused on the creation of user personas for the design of a nation-wide EHR, specifically the German "elektronische Patientenakte" (ePA). We employed qualitative methods, such as field analysis and expert workshops, to generate, assess, and refine a set of user personas that can cover the complexity of real-life familial care environments. We used an innovative bottom-up approach applying a whole new process for persona generation especially in the context of family management. Results: The research yielded an initial set of five personas that accurately represent fictional user types. Importantly, at least two of these personas encapsulate the unique challenges inherent in family care work. These results provide a foundation for future work, which can utilize these personas for EHR design, as well as for further evaluation and refinement.

Variation in opinions on coercion use among mental healthcare professionals: a questionnaire study

Introduction Even if coercive measures are widely applied in psychiatry and have numerous well-known drawbacks, there is limited known on the agreement among mental healthcare professionals’ opinions on their use. In a questionnaire study using standardized scenarios, we investigated variation in staff opinions on coercion. Methods In a web-based survey distributed to staff at three psychiatry hospitals, respondents were asked to consider if and what coercion to use by introducing two hypothetical scenarios involving involuntary psychiatric admission and in-hospital coercion. Results One hundred thirty-two out of 601 invited staff members responded to the survey (Response Rate = 22%). There was large variation in participating staff members’ opinions on how to best manage critical situations and what coercive measures were warranted. In the first scenario, 57% of respondents (n = 76) believed that the patient should be involuntarily admitted to hospital while the remaining respondents believed that the situation should be managed otherwise. Regarding the second scenario, 62% of respondents responded that some in-hospital coercion should be used. The majority of respondents believed that colleagues would behave similarly (60%) or with a tendency towards more coercion use (34%). Male gender, being nursing staff and having less coercion experience predicted being less inclined to choose involuntary hospital admission. Conclusion There is a high degree of variation in coercion use. This study suggests that this variation persists despite staff members being confronted with the same standardized situations. There is a need for evidence-based further guidance to minimize coercion in critical mental healthcare situations.

Women's expectations, preferences and needs in midwifery care – results from the qualitative Midwifery Care (MiCa) study: Childbirth and early parenthood

ObjectiveThe main goals of our study were (I) the investigation of expectations and preferences as well as (II) the determination of needs of women in regard to midwifery care. DesignDescriptive phenomenology was used to investigate the ways in which women experienced childbirth and early parenthood. A descriptive qualitative research design was chosen, using focus groups. Settingix online focus groups were carried out with 19 women for this part of the Midwifery Care (MiCa) study, mainly from the north of Germany. ParticipantsWomen shortly after birth, in puerperium and the first year after childbirth were recruited in Germany. A purposeful strategy according to maximum variation sampling was applied to reach diversity in the sample regarding age and previous children. Data were analysed using qualitative content analysis, according to Mayring, with support of the qualitative data analysis software MAXQDA 2022. FindingsSix main categories were derived for both childbirth and early parenthood: (a) involvement of family, (b) need for information, (c) physical and psychological aspects and (d) orientation in the healthcare system. In each group, one main category about provision of healthcare was developed: (e) care around childbirth and (f) midwifery care in early parenthood. Women attached great importance to the communication with midwives and favoured the involvement of their partners in the childbirth process and during parenting. Based on different experiences and inconsistency of information, women would prefer consistency in staff and communication as well as standardised information. ConclusionsFrom the user's perspective, midwifery care is crucial during childbirth and the child's first year of life. Current health care during and after childbirth and early parenthood lacks individualised care models, emotional support, adequate and professional communication between different health care providers, and consistency in midwifery care. Our findings should be translated into health care delivery with effective interprofessional teamwork within the continuity of midwifery care. Further quantitative research should analyse the individual healthcare situations of women in the reproductive phase of their life as well as of the applied healthcare models in order to personalise care and to improve healthcare quality.

Hybrid disease prediction approach leveraging digital twin and metaverse technologies for health consumer

Emerging from the convergence of digital twin technology and the metaverse, consumer health (MCH) is witnessing a transformative shift. The amalgamation of bioinformatics with healthcare Big Data has ushered in a new era of disease prediction models that harness comprehensive medical data, enabling the anticipation of illnesses even before the onset of symptoms. In this model, deep neural networks stand out because they improve accuracy remarkably by increasing network depth and making weight changes using gradient descent. Nonetheless, traditional methods face their own set of challenges, including the issues of gradient instability and slow training. In this case, the Broad Learning System (BLS) stands out as a good alternative. It gets around the problems with gradient descent and lets you quickly rebuild a model through incremental learning. One problem with BLS is that it has trouble extracting complex features from complex medical data. This makes it less useful in a wide range of healthcare situations. In response to these challenges, we introduce DAE-BLS, a novel hybrid model that marries Denoising AutoEncoder (DAE) noise reduction with the efficiency of BLS. This hybrid approach excels in robust feature extraction, particularly within the intricate and multifaceted world of medical data. Validation using diverse datasets yields impressive results, with accuracies reaching as high as 98.50%. DAE-BLS’s ability to rapidly adapt through incremental learning holds great promise for accurate and agile disease prediction, especially within the complex and dynamic healthcare scenarios of today.

Predicting Heart Diseases in IoT-Based Electronic Health Records: A Federated Learning Approach

Predicting heart diseases is important for finding them early and treating them effectively. We present a shared learning method for predicting heart diseases using IoT-based electronic health records (EHRs) in this work. Federated learning lets many autonomous IoT devices work together to train a model, while protecting the safety and security of the data. Proposed method uses the fact that IoT devices are spread out to train a global model for predicting heart disease without putting private EHR data in one place. With the EHR data, each IoT device learns a model locally and only sends model changes to a central computer. The computer takes all of these changes and improves the world model. This model is then sent back to the IoT devices to be improved even more. This looping process makes sure that the world model keeps getting better while keeping data private. The proposed method tested by using a real-world collection of EHRs from IoT devices in trials. We looked at how well our shared learning method worked compared to more standard centralized learning methods. Our results show that the pooled learning method makes predictions that are as good as or better than the other methods while protecting data privacy. It also looked at how different IoT device properties, like the amount of data they send and receive and their processing power, affect the shared learning process. It is discovered that devices with more processing power and more data add more to the improvement of the global model. This shows how important it is to choose the right devices in shared learning systems. The paper study shows that pooled learning can be used to predict heart diseases in IoT-based EHRs and that it works well. Our method uses the ability of IoT devices to work together to make accurate predictions while protecting data privacy. This makes it suitable for use in real-life healthcare situations.

Teaching stress reduction techniques including biofeedback for managing stress in medical students

IntroductionMedical students have been under immense pressure throughout their studies, impacting their mental health and academic performance. Stress reduction is a fundamental skill that all students require to manage their studies and lives efficiently. Biofeedback devices providing information about physiological states have been shown to aid stress reduction. Methods to reduce stress should be taught to medical students to help them tackle the challenges of medical school.ObjectivesOur goal was to teach stress reduction methods such as extracurricular activities and paced breathing aided by biofeedback training and its application in simulated healthcare situations to medical students.Methods15 medical students who completed medical physiology were recruited for an elective course of 7 sessions on practical techniques in stress management. One credit was offered to those who completed the course requirements consisting of participation in sessions and individual biofeedback training. Sessions (classes) consisted of presentations on good sleeping and eating patterns, group simulations of stressful hospital environments, visiting a science centre with interactive displays, an orchestra performance, and nature walks. Before biofeedback training, heart and respiration rates were taken individually by a biofeedback device during the first week of the course. Data was processed using a code created in statistical software. Heartbeats per minute and heart rate variability (HRV) for every 10 seconds were calculated and plotted on a graph. Two measurements were taken with each student: a baseline measurement for 10 minutes and another measurement during controlled breathing paced at 6 breaths per minute for 15 minutes, of which the first 10 minutes were used for calculation and plotting. Students provided narrative feedback in an essay submitted after the course was completed.Results5 males and 10 females from years 2-5 registered for the elective, and 12 participated in individually scheduled sessions. Heart beats per minute decreased, whereas HRV increased during paced breathing sessions in 83% of them. Most students reported feeling calm and drowsy during the sessions, and 2 students fell asleep by the end.Feedback from 11 students showed that the music session and the science centre visit were the highlights throughout the elective. Improvements recommended were to have a consistent time slot for all sessions and fewer simulations.Conclusions In concert with the literature, biofeedback training seems to be a feasible and effective method for relaxation in medical students. This method could be offered as part of mental health services for students. Data could be used to follow students’ progress and identify those requiring extra support. Providing them with avenues to de-stress while emphasizing activities outside medicine could boost their confidence and improve their coping skills.Disclosure of InterestNone Declared

Predicting Heart Diseases in IoT-Based Electronic Health Records: A Federated Learning Approach

Predicting heart diseases is important for finding them early and treating them effectively. We present a shared learning method for predicting heart diseases using IoT-based electronic health records (EHRs) in this work. Federated learning lets many autonomous IoT devices work together to train a model, while protecting the safety and security of the data. Proposed method uses the fact that IoT devices are spread out to train a global model for predicting heart disease without putting private EHR data in one place. With the EHR data, each IoT device learns a model locally and only sends model changes to a central computer. The computer takes all of these changes and improves the world model. This model is then sent back to the IoT devices to be improved even more. This looping process makes sure that the world model keeps getting better while keeping data private. The proposed method tested by using a real-world collection of EHRs from IoT devices in trials. We looked at how well our shared learning method worked compared to more standard centralized learning methods. Our results show that the pooled learning method makes predictions that are as good as or better than the other methods while protecting data privacy. It also looked at how different IoT device properties, like the amount of data they send and receive and their processing power, affect the shared learning process. It is discovered that devices with more processing power and more data add more to the improvement of the global model. This shows how important it is to choose the right devices in shared learning systems. The paper study shows that pooled learning can be used to predict heart diseases in IoT-based EHRs and that it works well. Our method uses the ability of IoT devices to work together to make accurate predictions while protecting data privacy. This makes it suitable for use in real-life healthcare situations.

Robotic-Assisted Ankle Rehabilitation Utilizing Electrical Stimulation and Virtual Reality Training Paradigms

This study investigates the ankle rehabilitation systems in great detail, including technical features, clinical considerations, patient-related factors, and economic factors. Using a parameterized method, different parameters were tested to find out how well, efficiently, and easily these systems could be used. It was looked at how technological features like robotic configuration, sensory feedback, and control methods can be used to make rehabilitation more personalized. To make sure the best results for patients, clinical considerations focused on practices based on evidence, safety features, and integration with clinical workflows. To look at the human-centered parts of ankle rehabilitation, things like user experience, adherence, and result measures were looked at. To find out if putting ankle rehabilitation systems into healthcare situations would be financially viable, economic factors like cost-effectiveness, reimbursement, and return on investment were looked at. Numbers were added to give quantitative information about each parameter, which made it easier to do a thorough review of ankle rehabilitation systems. Overall, this study gives important information to doctors, hospital managers, and others involved in improving the outcomes of ankle-related patients by choosing the best rehabilitation programs and making sure they are carried out properly.

Simulated role plays or field observation? Usability testing of a healthcare phrasebook

ABSTRACT The aim of this article is (1) to report on a usability study on the acceptability of a multilingual phrasebook for healthcare providers and (2) to compare the effectiveness and the efficiency of two key usability research methods: simulated role play and field observation. The usability study focused on the phrasebook’s acceptability (i.e., the extent to which the users consider it to be appropriate and serve its purpose), and consisted of two steps: first the acceptability was checked through simulated role play, involving 450 healthcare professionals, and second through field observation of five healthcare providers and 18 patients using the phrasebook in clinical settings. The results showed that the users are quite satisfied with the multilingual phrasebook; however, they also indicated that it hinders eye contact and does not offer sufficient support in more complex healthcare situations. The simulated roleplay and observation study both yielded comparable results. While the observation study was slightly more effective, if less efficient, the simulation study was very efficient and also highly effective, providing we focus only on the participants assuming the professional identity they have in real life, and thus proved to be a reliable alternative to observation methods in usability research.

Cultural Advocacy for Indigenous Individuals With Serious Illness.

Indigenous American (I.A.) individuals with serious illness and their families have unmet needs. Often, this group is viewed as a minority within a minority. Numerous health challenges exist within the I.A. populations resulting in dire health care situations. Historical trauma and mistrust of the healthcare system impacts access to quality palliative care by this marginalized population. Given the range of social, spiritual, and cultural issues, the interprofessional team needs increased knowledge specific to the I.A. population to ensure holistic, culturally sensitive care. Utilizing a case study, this article reviews of the needs of I.A. individuals with serious illness and essential skills. The aim is empower palliative care clinicians the knowledge to provide culturally sensitive and congruent care to I.A. individuals with serious illness and their community.

“You are a woman, so you understand what I mean”

Abstract This article analyses public service interpreters’ self-perceptions of the role played by their gender in their professional practice, a matter unexplored until now in interpreting studies. Through a thematic analysis of 95 responses to a qualitative online survey in Finland, the United Kingdom and Spain, this study identified (1) whether interpreters perceive their gender as significant in interpreter-mediated encounters; (2) in which situations interpreters believe their gender to be relevant; (3) the reasons why gender becomes significant in interpreter-mediated encounters, and (4) whether the interpreter’s gender has an impact on their credibility and trust-building. The results suggest that the interpreter’s gender plays a significant role in their interactions, having an impact on both the interpreter’s and the client’s experience. The participants highlight the significance of the interpreter’s gender, especially in healthcare situations, and discuss it in connection with the client’s level of comfort and preference; relatability based on shared experiences, gender biases and expectations; sexism; intersectionality, and the interpreter’s visibility. These results are examined with respect to the literature on gender in interpreting studies and paths for future research are suggested.

The Diversity Compass: a clinical ethics support instrument for dialogues on diversity in healthcare organizations

BackgroundIncreasing social pluralism adds to the already existing variety of heterogeneous moral perspectives on good care, health, and quality of life. Pluralism in social identities is also connected to health and care disparities for minoritized patient (i.e. care receiver) populations, and to specific diversity-related moral challenges of healthcare professionals and organizations that aim to deliver diversity-responsive care in an inclusive work environment. Clinical ethics support (CES) services and instruments may help with adequately responding to these diversity-related moral challenges. However, although various CES instruments exist to support healthcare professionals with dealing well with morally challenging situations in healthcare, current tools do not address challenges specifically related to moral pluralism and intersectional aspects of diversity and social justice issues. This article describes the content and developmental process of a novel CES instrument called the Diversity Compass. This instrument was designed with and for healthcare professionals to dialogically address and reflect on moral challenges related to intersectional aspects of diversity and social justice issues that they experience in daily practice.MethodsWe used a participatory development design to develop the Diversity Compass at a large long-term care organization in a major city in the Netherlands. Over a period of thirteen months, we conducted seven focus groups with healthcare professionals and peer-experts, carried out five expert interviews, and facilitated four meetings with a community of practice consisting of various healthcare professionals who developed and tested preliminary versions of the instrument throughout three cycles of iterative co-creation.ResultsThe Diversity Compass is a practical, dialogical CES instrument that is designed as a small booklet and includes an eight-step deliberation method, as well as a guideline with seven recommendations to support professionals with engaging in dialogue when they are confronted with diversity-related moral challenges. The seven recommendations are key components in working toward creating an inclusive and safe space for dialogue to occur.ConclusionsThe Diversity Compass seeks to support healthcare professionals and organizations in their efforts to facilitate awareness, moral learning and joint reflection on moral challenges related to diversity and social justice issues. It is the first dialogical CES instrument that specifically acknowledges the role of social location in shaping moral perspectives or experiences with systemic injustices. However, to make healthcare more just, an instrument like the Diversity Compass is not enough on its own. In addition to the Diversity Compass, a systemic and structural approach to social justice issues in healthcare organizations is needed in order to foster a more inclusive, safe and diversity-responsive care and work environment in health care organizations.

A review of magnetic nanoparticles used in nanomedicine

The ability to manipulate magnetic nanoparticles with external magnetic fields and their compatibility with biological systems make them versatile tools in the field of nanomedicine. Recently, the integration of various nanotechnologies with biomedical science, pharmacology, and clinical practice has led to the emergence of the discipline of nanomedicine. Owing to the special qualities of nanoparticles and related nanostructures, their uses in controlled drug and gene delivery, imaging, medical diagnostics, monitoring therapeutic outcomes, and supporting medical interventions offer a fresh approach to difficult problems in difficult areas like the treatment of cancer or crippling neurological diseases. The potential for multi-functionality and advanced targeting tactics in nanoparticle products exists. It may maximize the effectiveness of current anticancer drugs by enhancing the pharmacodynamic and pharmacokinetic characteristics of conventional therapies. These nanometer-sized substances’ distinctive electrical, magnetic, and optical characteristics have opened up a wide range of biological uses. As they may be used in healthcare situations due to their bioactivity, iron-oxide-based magnetic nanoparticles, in particular, have been shown to be incredibly useful deep-tissue scanning tools. In addition to having a broader operating temperature range, smaller size, reduced toxicity, easier processing, and less cost of production, newer nanoparticles (MNPs) also offer other benefits. MNPs offer a lot of promise for use in clinical settings because of a variety of exceptional and distinctive chemical and biological features. Modern targeting techniques and nanoparticles studied in clinical trials are included in this review. It highlights the difficulties in applying nanomedicine items and transferring them from the laboratory to the clinical environment. It also addresses topics of nanoparticle design that might create new clinical applications for nanomedicine items. Magnetic nanoparticles used in nanomedicine offer several novel and promising features that make them valuable tools for various applications. When utilized in nanomedicine, magnetic nanoparticles have a number of exciting new properties that make them useful instruments for a range of uses. Drug delivery, hyperthermia therapy, magnetic resonance imaging contrast agents, diagnostic imaging and monitoring, theranostic applications, biocompatibility and biodegradability, remote control and manipulation, and responsive nanoparticles are the main factors that add to their novelty. In general, the amalgamation of nanoscale characteristics and magnetic properties presents a multitude of opportunities for inventive medical applications, offering focused, effective, and least intrusive approaches to diagnosis and treatment. The sector is still investigating novel ways to increase the safety and efficacy of magnetic nanoparticles in nanomedicine. The purpose of this article is to provide basic details about magnetic nanoparticles and the characteristics of these particles in biomedical applications. The features of these nanoparticles in medication delivery and their numerous uses have received extra focus in the study. It seeks to summarize current advancements in MNPs for medical applications and examine the possibilities of MNPs in tumor therapeutic applications, in addition to future study opportunities.

A Modified and Effective Blockchain Model for E-Healthcare Systems

The development of e-healthcare systems requires the application of advanced technologies, such as blockchain technology. The main challenge of applying blockchain technology to e-healthcare is to handle the impact of the delay that results from blockchain procedures during the communication and voting phases. The impacts of latency in blockchains negatively influence systems’ efficiency, performance, real-time processing, and quality of service. Therefore, this work proposes a modified model of a blockchain that allows delays to be avoided in critical situations in healthcare. Firstly, this work analyzes the specifications of healthcare data and processes to study and classify healthcare transactions according to their nature and sensitivity. Secondly, it introduces the concept of a fair-proof-of-stake consensus protocol for block creation and correctness procedures rather than famous ones such as proof-of-work or proof-of-stake. Thirdly, the work presents a simplified procedure for block verification, where it classifies transactions into three categories according to the time period limit and trustworthiness level. Consequently, there are three kinds of blocks, since every category is stored in a specific kind of block. The ideas of time period limits and trustworthiness fit with critical healthcare situations and the authority levels in healthcare systems. Therefore, we reduce the validation process of the trusted blocks and transactions. All proposed modifications help to reduce computational costs, speed up processing times, and enhance security and privacy. The experimental results show that the total execution time using a modified blockchain is reduced by about 49% compared to traditional blockchain models. Additionally, the number of messages using modified blockchain is reduced by about 53% compared to the traditional blockchain model.

Cochlear implant and tinnitus

Cochlear implant (CI) treatment is now established as asuccessful standard of care for auditory rehabilitation of profoundly deaf or severe hearing loss patients. CI candidates with tinnitus also benefit from improved health-related quality of life (HRQoL) and tinnitus burden. Current CI indications include bilateral (double-sided) profound hearing loss and deafness (DSD), unilateral (single-sided) deafness (SSD), and asymmetric hearing loss (AHL). The new and expanded indications for cochlear implants result in different healthcare situations, which may also be associated with differences in tinnitus burden before and after CI treatment. In this article, we discuss the prevalence of tinnitus in different patient groups and the influence of CI on tinnitus prevalence and severity in these groups. In addition, further therapeutic options for tinnitus suppression based on the CI principle are presented, including the development of an anti-tinnitus implant (proof of concept).

Multilingual communication in Speech Language Therapy

Multilingualism can both enrich and complicate interactions in health care. Several studies (Ferguson, 2002; Jacobs, 2017) point out that language differences between care providers and patients can lead to less access to and lower quality of care. More specifically, challenges regarding communication, mutual understanding and shared decision making are often present (Cox & Maryns, 2021; Schouten et al., 2017) in health care situations. A specific type of care where communication is both instrument and goal of therapy is Speech language therapy (SLT). This profession offers guidance for people who experience difficulties with communication. In the daily practice of speech language therapists (SLTs) clients are vulnerable in their communication in different ways (Blackstone, 2015). For example, in multiethnic cities in the Netherlands many people have limited language proficiency in Dutch and they can also have a communication disorder These converging communication vulnerabilities form a challenge for SLTs. Several studies within the field of SLT have been performed to improve the diagnosis and treatment of complex multilingual cases (Hyter & Salas-Provance, 2023), but little research has been done on the actual interaction during those multilingual encounters (Hand, 2006). Although SLTs are experts in communication, experiences from the work field indicate that these professionals often feel less competent when interacting with multilingual clients or their parents (Lagendijk, 2021). As these situations occur very often in SLT practice and are quite complex due to interfering communication vulnerabilities, they need to be critically explored. The current PhD study LIMINA (Logos In Multilingual InterAction) aims to gain insight into multilingual communication in Speech language therapy in order to enhance inclusive care. By carrying out various research methods (discourse analysis, in depth interviews, focus groups and design based research) different perspectives in the SLT setting are being explored. Data from the actual interaction will be compared and synthesized with the perspectives of clients and professionals in order to create a kaleidoscopic view. Moreover, the project intends to design a practical intervention in co-creation with representatives from the work field in order to enhance inclusive communication in SLT care. For the purpose of the first sub study, students of the Rotterdam University of Applied Sciences collected transcripts from conversations between SLTs and parents, representing their underaged children. Two datasets were composed for the current analysis: a) transcripts of intake sessions (n = 15) and b) transcripts of test results discussions (n = 18). Parents have diverse linguistic backgrounds and most of the conversations took place in Dutch, without an interpreter. By performing a critical discourse analysis (Ten Thije, 2001) multilingual interactions are currently being reconstructed in order to gain insight in patterns, structures and (un)successful actions. Preliminary results show that both SLTs and parents use several interactional strategies for inclusive multilingualism (Backus, 2013) during consults. Mostly supporting materials, such as reports, were used by the SLT to facilitate the verbal interaction; especially during the test result discussions. Also gesturing, writing and drawing were often used as strategies to facilitate the conversation. In five (out of fifteen) intake sessions no strategies were used during interaction. These parents were considered to be sufficiently fluent in the Dutch language by the researchers who analyzed the transcripts. In none of the test result discussions (n = 18) an interpreter was present to enhance understanding. First conclusions regarding inclusive multilingualism in SLT care reveal that although participants choose different ways to support their verbal message, this does not guarantee an adequate transfer of knowledge within the institutional setting of Speech language therapy. Specific conversational goals from both SLTs and parents were often not achieved during the intake sessions and test results discussions. This seems to correspond with the earlier reported experiences of SLTs (Lagendijk, 2021) and underlines the importance of the current study. The present poster gives a textual and graphical overview of the research design for the overarching PhD study LIMINA. The indicated colors represent the different sub studies and the image shows an authentic fragment of a resolved misunderstanding between a parent and a speech language therapist. Furthermore, the poster provides a table of preliminary results concerning the interactional strategies used by SLTs and parents during institutional encounters.