Improving medication prescribing-related outcomes for vulnerable elderly in transitions on high-risk medications (IMPROVE-IT HRM): a pilot randomized trial protocol.

BACKGROUND: Seniors with recurrent hospitalizations who are taking multiple medications including high-risk medications are at particular risk for serious adverse medication events. We will assess whether an expert Clinical Pharmacology and Toxicology (CPT) medication management intervention during hospitalization with follow-up post-discharge and communication with circle of care is feasible and can decrease drug therapy problems amongst this group. METHODS: The design is a pragmatic pilot randomized trial with 1:1 patient-level concealed randomization with blinded outcome assessment and data analysis. Participants will be adults 65 years and older admitted to internal medicine services for more than 2 days, who have had at least one other hospitalization in the prior year, taking five or more chronic medications including at least one high-risk medication. The CPT intervention identifies medication targets; completes consult, including priorities for improving prescribing negotiated with the patient; starts the care plan; ensures a detailed discharge medication reconciliation and circle-of-care communication; and sees the patient at least twice after hospital discharge via virtual visits to consolidate the care plan in the community. Control group receives usual care. Primary outcomes are feasibility - recruitment, retention, costs, and clinical - number of drug therapy problems improved, with secondary outcomes examining coordination of transitions in care, quality of life, and healthcare utilization and costs. Follow-up is to 3-month posthospital discharge. DISCUSSION: If results support feasibility of ramp-up and promising clinical outcomes, a follow-up definitive trial will be organized using a developing national platform and medication appropriateness network. Since the intervention allows a very scarce medical specialty expertise to be offered via virtual care, there is potential to improve the safety, outcomes, and cost of care widely. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov identifier: NCT04077281.

Moniz Game: Usability and User Experience Evaluation of a Musical Game for Motor Coordination.

Purpose: The objective of this research was to develop a musical digital game for rehabilitation of upper limb and to verify its usability and user experience with professionals in the field (physical therapists). Materials and Methods: Thirty working professionals were recruited to evaluate the system. The usability was evaluated with the System Usability Scale (SUS) and the user experience was verified with the Game Flow scale. Results: The overall score of the SUS scale was 88.67 (±9.129); this score is interpreted as "Best Imaginable" (86-100). The user experience rating had most of its domains equal or higher than 4, which indicates that all the requirements for a good user experience were present in the game. Conclusions: The Moniz Game proved to be a game with good usability and can be a tool for application in clinical practice regarding motor coordination. However, further studies are needed to evaluate the effect of the Moniz Game on motor coordination in patients with neurological dysfunctions.

Fostering effective and sustainable scientific collaboration and knowledge exchange: a workshop-based approach to establish a national ecological observatory network (NEON) domain-specific user group.

The decision to establish a network of researchers centers on identifying shared research goals. Ecologically specific regions, such as the USA's National Ecological Observatory Network's (NEON's) eco-climatic domains, are ideal locations by which to assemble researchers with a diverse range of expertise but focused on the same set of ecological challenges. The recently established Great Lakes User Group (GLUG) is NEON's first domain specific ensemble of researchers, whose goal is to address scientific and technical issues specific to the Great Lakes Domain 5 (D05) by using NEON data to enable advancement of ecosystem science. Here, we report on GLUG's kick off workshop, which comprised lightning talks, keynote presentations, breakout brainstorming sessions and field site visits. Together, these activities created an environment to foster and strengthen GLUG and NEON user engagement. The tangible outcomes of the workshop exceeded initial expectations and include plans for (i) two journal articles (in addition to this one), (ii) two potential funding proposals, (iii) an assignable assets request and (iv) development of classroom activities using NEON datasets. The success of this 2.5-day event was due to a combination of factors, including establishment of clear objectives, adopting engaging activities and providing opportunities for active participation and inclusive collaboration with diverse participants. Given the success of this approach we encourage others, wanting to organize similar groups of researchers, to adopt the workshop framework presented here which will strengthen existing collaborations and foster new ones, together with raising greater awareness and promotion of use of NEON datasets. Establishing domain specific user groups will help bridge the scale gap between site level data collection and addressing regional and larger ecological challenges.

REPAIRS Delphi: A UK and Ireland Consensus Statement on the Management of Infected Arterial Pseudoaneurysms Secondary to Groin Injecting Drug Use.

OBJECTIVE: Consensus guidelines on the optimal management of infected arterial pseudoaneurysms secondary to groin injecting drug use are lacking. This pathology is a problem in the UK and globally, and operative management options remain contentious. This study was designed to establish consensus to promote better management of these patients, drawing on the expert experience of those in a location with a high prevalence of illicit drug use. METHODS: A three round modified Delphi was undertaken, systematically surveying consultant vascular surgeons in the UK and Ireland using an online platform. Seventy five vascular surgery units were invited to participate, with one consultant providing the unit consensus practice. Round one responses were thematically analysed to generate statements for round two. These statements were evaluated by participants using a five point Likert scale. Consensus was achieved at a threshold of 70% or more agreement or disagreement. Those statements not reaching consensus were assessed and modified for round three. The results of the Delphi process constituted the consensus statement. RESULTS: Round one received 64 (86%) responses, round two 59 (79%) responses, and round three 62 (83%) responses; 73 out of 75 (97%) units contributed. Round two comprised 150 statements and round three 24 statements. Ninety one statements achieved consensus agreement and 15 consensus disagreement. The Delphi statements covered sequential management of these patients from diagnosis and imaging, antibiotics and microbiology, surgical approach, wound management, follow up, and additional considerations. Pre-operative imaging achieved consensus agreement (97%), with computerised tomography angiogram being the modality of choice (97%). Ligation and debridement without arterial reconstruction was the preferred approach at initial surgical intervention (89%). Multidisciplinary management, ensuring holistic care and access to substance use services, also gained consensus agreement. CONCLUSION: This comprehensive consensus statement provides a strong insight into the standard of care for these patients.

User satisfaction with child and adolescent mental health services: the association between user satisfaction and clinical outcomes.

BACKGROUND: This study aimed to examine the association between user satisfaction and clinical outcomes with child and adolescent mental health services (CAMHS) from the perspective of young people and their parents. The evidence bases for CAMHS user satisfaction measures are limited, with few studies investigating the link between user satisfaction and clinical outcomes. In particular, the perspectives of young people are missing. METHODS: The parent and youth versions of the Experience of Service Questionnaire (ESQ), which evaluates the factors of general satisfaction (GS), satisfaction with care (SWC) and satisfaction with environment (SWE), were used to measure user satisfaction. The outcome measures were scores on the Strengths and Difficulties Questionnaire (SDQ), Children's Global Assessment Scale (CGAS), and Health of the Nation Outcome Scales for Children and Adolescents (HoNOSCA). Hierarchical regression analysis was conducted on data collected from 233 young people and 495 parents who utilized CAMHS services. RESULTS: GS and SWC predicted outcomes for both young people (ΔR2 = 0.08, p <.05) and parents (ΔR2 = 0.01, p <.05), indicating that user satisfaction had a significant impact on clinical outcomes for CAMHS users. In addition, GS and SWC significantly predicted young people-reported outcomes in the interaction model (ΔR2 = 0.10, p <.05), while no significant association was found with parent-reported outcomes (ΔR2 = 0.02, p =.09). CONCLUSION: User satisfaction, particularly for young people, has a significant impact on clinical outcomes. The causal relationship between user satisfaction and mental health outcomes requires further study.

Understanding Senior Adults' Needs, Preferences, and Experiences of Commercial Exergames for Health: Usability Study.

BACKGROUND: Many senior adults are at risk of mental and physical disorders due to a lack of sufficient exercise. Therefore, adherent exercise should be urgently promoted to improve senior adults' muscle strength, preventing falls and conditions caused by physical and cognitive decline. However, off-the-shelf exercise games, so-called exergames, are mainly targeted at the younger generation or children, while senior adults are neglected, when this age group strongly needs exercise. Exergames could serve as a health intervention for promoting exercise. OBJECTIVE: This study aimed to investigate senior adults' experience, perceptions, and acceptance of game technology to promote exercise in order to suggest game design guidelines. METHODS: In this usability study, participants engaged in playing Nintendo Switch and Xbox Kinect games, after which semistructured interviews were conducted. Before the gameplay, the participants provided their background information, exercise habits, and use of technology products. Next, all participants completed a workshop including 3 activities (brief instructions on how to play the games: 20 minutes; playing the selected exergames: 80 minutes; semistructured interviews: 20 minutes) for 2 hours a day for 3 days each. The participants played the latest Nintendo Switch games (eg, Just Dance, Boxing, Ring Fit Adventure) and Xbox Kinect games (eg, Kinect Adventures!, Mini Games). Just Dance, Zumba, and Boxing were played in activity 1; Ring Fit Adventure and Mini Games in activity 2; and Kinect Adventures! in activity 3. Reflexive thematic analysis was applied to identify the relative themes generated from the interviews. RESULTS: In total, 22 participants (mean age 70.4, SD 6.1 years) were enrolled in the workshop in May 2021. The results of the generated themes included incomprehension of game instructions, psychological perception of game technology, and game art preferences. The subthemes generated from game art preferences included favorite game genres, characters, and scenes. CONCLUSIONS: There is a significant need for customized game tutorials considering senior adults' cognitive and physical aging. Furthermore, the adventure game genre is preferable to other games. Humanlike game characters are preferable, especially those with a fit and healthy body shape. Nature scenes are more enjoyable than indoor stages or rooms. Furthermore, the game intensity design and playing time should be carefully planned to meet the World Health Organization's criteria for physical activity in older adults. Intelligent recommendation systems might be helpful to support older adults with various health conditions. The guidelines suggested in this study might be beneficial for game design, exercise training, and game technology adoption of exergames for older adults to improve health.

A Technological Tool Aimed at Self-Care in Patients With Multimorbidity: Cross-Sectional Usability Study.

BACKGROUND: Information and communication technologies (ICTs) have been positioned as useful tools to facilitate self-care. The interaction between a patient and technology, known as usability, is particularly important for achieving positive health outcomes. Specific characteristics of patients with chronic diseases, including multimorbidity, can affect their interaction with different technologies. Thus, studying the usability of ICTs in the field of multimorbidity has become a key element to ensure their relevant role in promoting self-care. OBJECTIVE: The aim of this study was to analyze the usability of a technological tool dedicated to health and self-care in patients with multimorbidity in primary care. METHODS: A descriptive observational cross-sectional usability study was performed framed in the clinical trial in the primary care health centers of Madrid Health Service of the TeNDER (Affective Based Integrated Care for Better Quality of Life) project. The TeNDER technological tool integrates sensors for monitoring physical and sleep activity along with a mobile app for consulting the data collected and working with self-management tools. This project included patients over 60 years of age who had one or more chronic diseases, at least one of which was mild-moderate cognitive impairment, Parkinson disease, or cardiovascular disease. From the 250 patients included in the project, 38 agreed to participate in the usability study. The usability variables investigated were effectiveness, which was determined by the degree of completion and the total number of errors per task; efficiency, evaluated as the average time to perform each task; and satisfaction, quantified by the System Usability Scale. Five tasks were evaluated based on real case scenarios. Usability variables were analyzed according to the sociodemographic and clinical characteristics of patients. A logistic regression model was constructed to estimate the factors associated with the type of support provided for task completion. RESULTS: The median age of the 38 participants was 75 (IQR 72.0-79.0) years. There was a slight majority of women (20/38, 52.6%) and the participants had a median of 8 (IQR 7.0-11.0) chronic diseases. Thirty patients completed the usability study, with a usability effectiveness result of 89.3% (134/150 tasks completed). Among the 30 patients, 66.7% (n=20) completed all tasks and 56.7% (17/30) required personalized help on at least one task. In the multivariate analysis, educational level emerged as a facilitating factor for independent task completion (odds ratio 1.79, 95% CI 0.47-6.83). The median time to complete the total tasks was 296 seconds (IQR 210.0-397.0) and the median satisfaction score was 55 (IQR 45.0-62.5) out of 100. CONCLUSIONS: Although usability effectiveness was high, the poor efficiency and usability satisfaction scores suggest that there are other factors that may interfere with the results. Multimorbidity was not confirmed to be a key factor affecting the usability of the technological tool. TRIAL REGISTRATION: Clinicaltrials.gov NCT05681065; https://clinicaltrials.gov/study/NCT05681065.

Feasibility, Acceptability, and Preliminary Efficacy of a Smartphone App-Led Cognitive Behavioral Therapy for Depression Under Therapist Supervision: Open Trial.

BACKGROUND: Major depressive disorder affects approximately 1 in 5 adults during their lifetime and is the leading cause of disability worldwide. Yet, a minority receive adequate treatment due to person-level (eg, geographical distance to providers) and systems-level (eg, shortage of trained providers) barriers. Digital tools could improve this treatment gap by reducing the time and frequency of therapy sessions needed for effective treatment through the provision of flexible, automated support. OBJECTIVE: This study aimed to examine the feasibility, acceptability, and preliminary clinical effect of Mindset for Depression, a deployment-ready 8-week smartphone-based cognitive behavioral therapy (CBT) supported by brief teletherapy appointments with a therapist. METHODS: This 8-week, single-arm open trial tested the Mindset for Depression app when combined with 8 brief (16-25 minutes) video conferencing visits with a licensed doctoral-level CBT therapist (n=28 participants). The app offers flexible, accessible psychoeducation, CBT skills practice, and support to patients as well as clinician guidance to promote sustained engagement, monitor safety, and tailor treatment to individual patient needs. To increase accessibility and thus generalizability, all study procedures were conducted remotely. Feasibility and acceptability were assessed via attrition, patient expectations and feedback, and treatment utilization. The primary clinical outcome measure was the clinician-rated Hamilton Depression Rating Scale, administered at pretreatment, midpoint, and posttreatment. Secondary measures of functional impairment and quality of life as well as maintenance of gains (3-month follow-up) were also collected. RESULTS: Treatment credibility (week 4), expectancy (week 4), and satisfaction (week 8) were moderate to high, and attrition was low (n=2, 7%). Participants self-reported using the app or practicing (either on or off the app) the CBT skills taught in the app for a median of 50 (IQR 30-60; week 4) or 60 (IQR 30-90; week 8) minutes per week; participants accessed the app on an average 36.8 (SD 10.0) days and completed a median of 7 of 8 (IQR 6-8) steps by the week 8 assessment. The app was rated positively across domains of engagement, functionality, aesthetics, and information. Participants' depression severity scores decreased from an average Hamilton Depression Rating Scale score indicating moderate depression (mean 19.1, SD 5.0) at baseline to a week 8 mean score indicating mild depression (mean 10.8, SD 6.1; d=1.47; P<.001). Improvement was also observed for functional impairment and quality of life. Gains were maintained at 3-month follow-up. CONCLUSIONS: The results show that Mindset for Depression is a feasible and acceptable treatment option for individuals with major depressive disorder. This smartphone-led treatment holds promise to be an efficacious, scalable, and cost-effective treatment option. The next steps include testing Mindset for Depression in a fully powered randomized controlled trial and real-world clinical settings. TRIAL REGISTRATION: ClinicalTrials.gov NCT05386329; https://clinicaltrials.gov/study/NCT05386329?term=NCT05386329.

Clinical Remote Monitoring of Individuals With Spinal Cord Injury at Risk for Pressure Injury Recurrence Using mHealth: Protocol for a Pilot, Pragmatic, Hybrid Implementation Trial.

BACKGROUND: Pressure injuries are one of the most challenging secondary conditions for individuals with spinal cord injuries and related disorders (SCI/D) owing to inherent, lifelong risk factors that include a lack of sensory and motor function below the level of injury and reliance on a wheelchair for daily mobility, resulting in prolonged periods of sitting. Although many factors contribute to the development of pressure injuries, the pressure between the skin and a surface is always a factor and the development of injury is dependent on the magnitude and duration of the pressure. Clinically, broad recommendations for relieving pressure are used because we know very little about the unique day-to-day life patterns of the individual wheelchair user. Typically, it is after the occurrence of a pressure injury that the therapist will check equipment fit and the effectiveness of pressure offloading and ask about other surfaces they sit on in their home and community. This time-lapsed, largely self-reported data are fraught with recall bias and inaccuracies that the therapist incorporates into a plan of care. OBJECTIVE: This study's objective is to pilot-test the implementation and clinical effectiveness of a telehealth model of care combined with our mobile health (mHealth) Assisted Weight-Shift device for remote monitoring of factors related to maintaining skin health and wheelchair setup. Our overall hypothesis is that this study will result in an effective implementation plan, and the enhanced connected model of care using remote monitoring of pressure management will result in pilot-level, improved clinical outcomes for adults with spinal cord injury at high risk for pressure injury recurrence. METHODS: For all aims, we will use a mixed methods design using an exploratory, sequential approach to include the strengths of both qualitative and quantitative data. For aims 1 and 2, we will iteratively collect qualitative data from therapists, patients with SCI/D, and other stakeholders. For aim 3, we will perform a hybrid effectiveness-implementation randomized controlled trial to pilot-test the intervention. The projected results include an iteratively developed and tested implementation plan that meets moderate to high levels of acceptability, feasibility, and appropriateness. Additionally, the pilot trial results are expected to show positive trends in relevant clinical outcomes related to reduced pressure injury incidence, recurrence, and improved healing when compared with the standard of care. RESULTS: Currently, 6 participants have been recruited for our aim-1 qualitative study. CONCLUSIONS: This study will expand upon our previous study to move the Assisted Weight-Shift system into routine clinical care, which was a strong desire of adults with SCI/D for improved individualized care plans to prevent pressure injuries. The results of this study will guide the next steps in a full, hybrid effectiveness-implementation trial with the goal of improving care to prevent pressure injuries. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/51849.

Development of a Trusted Third Party at a Large University Hospital: Design and Implementation Study.

Background: Pseudonymization has become a best practice to securely manage the identities of patients and study participants in medical research projects and data sharing initiatives. This method offers the advantage of not requiring the direct identification of data to support various research processes while still allowing for advanced processing activities, such as data linkage. Often, pseudonymization and related functionalities are bundled in specific technical and organization units known as trusted third parties (TTPs). However, pseudonymization can significantly increase the complexity of data management and research workflows, necessitating adequate tool support. Common tasks of TTPs include supporting the secure registration and pseudonymization of patient and sample identities as well as managing consent. Objective: Despite the challenges involved, little has been published about successful architectures and functional tools for implementing TTPs in large university hospitals. The aim of this paper is to fill this research gap by describing the software architecture and tool set developed and deployed as part of a TTP established at Charité - Universitätsmedizin Berlin. Methods: The infrastructure for the TTP was designed to provide a modular structure while keeping maintenance requirements low. Basic functionalities were realized with the free MOSAIC tools. However, supporting common study processes requires implementing workflows that span different basic services, such as patient registration, followed by pseudonym generation and concluded by consent collection. To achieve this, an integration layer was developed to provide a unified Representational state transfer (REST) application programming interface (API) as a basis for more complex workflows. Based on this API, a unified graphical user interface was also implemented, providing an integrated view of information objects and workflows supported by the TTP. The API was implemented using Java and Spring Boot, while the graphical user interface was implemented in PHP and Laravel. Both services use a shared Keycloak instance as a unified management system for roles and rights. Results: By the end of 2022, the TTP has already supported more than 10 research projects since its launch in December 2019. Within these projects, more than 3000 identities were stored, more than 30,000 pseudonyms were generated, and more than 1500 consent forms were submitted. In total, more than 150 people regularly work with the software platform. By implementing the integration layer and the unified user interface, together with comprehensive roles and rights management, the effort for operating the TTP could be significantly reduced, as personnel of the supported research projects can use many functionalities independently. Conclusions: With the architecture and components described, we created a user-friendly and compliant environment for supporting research projects. We believe that the insights into the design and implementation of our TTP can help other institutions to efficiently and effectively set up corresponding structures.

Large Language Models and User Trust: Consequence of Self-Referential Learning Loop and the Deskilling of Health Care Professionals.

As the health care industry increasingly embraces large language models (LLMs), understanding the consequence of this integration becomes crucial for maximizing benefits while mitigating potential pitfalls. This paper explores the evolving relationship among clinician trust in LLMs, the transition of data sources from predominantly human-generated to artificial intelligence (AI)-generated content, and the subsequent impact on the performance of LLMs and clinician competence. One of the primary concerns identified in this paper is the LLMs' self-referential learning loops, where AI-generated content feeds into the learning algorithms, threatening the diversity of the data pool, potentially entrenching biases, and reducing the efficacy of LLMs. While theoretical at this stage, this feedback loop poses a significant challenge as the integration of LLMs in health care deepens, emphasizing the need for proactive dialogue and strategic measures to ensure the safe and effective use of LLM technology. Another key takeaway from our investigation is the role of user expertise and the necessity for a discerning approach to trusting and validating LLM outputs. The paper highlights how expert users, particularly clinicians, can leverage LLMs to enhance productivity by off-loading routine tasks while maintaining a critical oversight to identify and correct potential inaccuracies in AI-generated content. This balance of trust and skepticism is vital for ensuring that LLMs augment rather than undermine the quality of patient care. We also discuss the risks associated with the deskilling of health care professionals. Frequent reliance on LLMs for critical tasks could result in a decline in health care providers' diagnostic and thinking skills, particularly affecting the training and development of future professionals. The legal and ethical considerations surrounding the deployment of LLMs in health care are also examined. We discuss the medicolegal challenges, including liability in cases of erroneous diagnoses or treatment advice generated by LLMs. The paper references recent legislative efforts, such as The Algorithmic Accountability Act of 2023, as crucial steps toward establishing a framework for the ethical and responsible use of AI-based technologies in health care. In conclusion, this paper advocates for a strategic approach to integrating LLMs into health care. By emphasizing the importance of maintaining clinician expertise, fostering critical engagement with LLM outputs, and navigating the legal and ethical landscape, we can ensure that LLMs serve as valuable tools in enhancing patient care and supporting health care professionals. This approach addresses the immediate challenges posed by integrating LLMs and sets a foundation for their maintainable and responsible use in the future.

Application of a user experience design approach for an EHR-based clinical decision support system.

Objective: We applied a user experience (UX) design approach to clinical decision support (CDS) tool development for the specific use case of pediatric asthma. Our objective was to understand physicians' workflows, decision-making processes, barriers (ie, pain points), and facilitators to increase usability of the tool. Materials and methods: We used a mixed-methods approach with semi-structured interviews and surveys. The coded interviews were synthesized into physician-user journey maps (ie, visualization of a process to accomplish goals) and personas (ie, user types). Interviews were conducted via video. We developed physician journey maps and user personas informed by their goals, systems interactions, and experiences with pediatric asthma management. Results: The physician end-user personas identified were: efficiency, relationship, and learning. Features of a potential asthma CDS tool sought varied by physician practice type and persona. It was important to the physician end-user that the asthma CDS tool demonstrate value by lowering workflow friction (ie, difficulty or obstacles), improving the environment surrounding physicians and patients, and using it as a teaching tool. Customizability versus standardization were important considerations for uptake. Discussion: Different values and motivations of physicians influence their use and interaction with the EHR and CDS tools. These different perspectives can be captured by applying a UX design approach to the development process. For example, with the importance of customizability, one approach may be to build a core module with variations depending on end-user preference. Conclusion: A UX approach can drive design to help understand physician-users and meet their needs; ultimately with the goal of increased uptake.

A user DNS fingerprint dataset.

Using a user DNS fingerprint allows one to identify a specific network user regardless of the knowledge of his IP address. This method is proper, for example, when examining the behavior of a monitored network user in more depth. In contrast to other studies, this work introduces a dataset for possible user identification based only on the knowledge of its DNS fingerprint created from the previously sent DNS queries. We created a large dataset from the real network traffic of a metropolitan Internet service provider. The dataset was created from 2.3 billion DNS queries representing 6.2 million different domain names. The data collection took place over three months from 12/2023 to 02/2024. The dataset contains a detailed user activity description in the sense of overall daily activity statistics and detailed 24 h activity statistics. Each dataset record contains a list of 1137 classification attributes. The absolutely unique feature of this data set is the classification of user activity based on categories of content accessed by a user. The new dataset can be used for the creation of machine learning models, allowing the identification of a specific user without direct knowledge of their IP addresses or additional network location information. The dataset can also serve as a reference dataset for the creation of DNS fingerprints of users.

The Dual Importance of Virtual Reality Usability in Rehabilitation: A Focus on Therapists and Patients.

Virtual reality (VR) has advanced in medical education and rehabilitation from basic graphical applications due to its ability to generate a virtual three-dimensional (3D) environment. This environment is mostly used to practice professional skills, plan surgery procedures, simulate surgeries, display 3D anatomy, and rehabilitate various disorders. VR has transformed the field of rehabilitation therapy by providing immersive and engaging experiences that go beyond traditional bounds, significantly improving patient care and therapeutic results. Considering the direct impact of VR on the efficacy of the treatment for both therapists and patients, its dual significance for usability and user experience cannot be overstated. The purpose of this article is to determine the synergistic association between VR accessibility and the rehabilitation process, highlighting the significance of VR technology in designing the future of rehabilitation therapy and demonstrating how advancing VR technology can improve therapeutic outcomes despite overcoming obstacles encountered during VR usage. In conclusion, VR offers a personalized, efficient, interesting, and engaging rehabilitative environment for patients, while also assisting therapists in cultivating empathy and efficiency and encouraging innovative approaches in treatment procedures.

Learning-based personalisation of robot behaviour for robot-assisted therapy.

During robot-assisted therapy, a robot typically needs to be partially or fully controlled by therapists, for instance using a Wizard-of-Oz protocol; this makes therapeutic sessions tedious to conduct, as therapists cannot fully focus on the interaction with the person under therapy. In this work, we develop a learning-based behaviour model that can be used to increase the autonomy of a robot's decision-making process. We investigate reinforcement learning as a model training technique and compare different reward functions that consider a user's engagement and activity performance. We also analyse various strategies that aim to make the learning process more tractable, namely i) behaviour model training with a learned user model, ii) policy transfer between user groups, and iii) policy learning from expert feedback. We demonstrate that policy transfer can significantly speed up the policy learning process, although the reward function has an important effect on the actions that a robot can choose. Although the main focus of this paper is the personalisation pipeline itself, we further evaluate the learned behaviour models in a small-scale real-world feasibility study in which six users participated in a sequence learning game with an assistive robot. The results of this study seem to suggest that learning from guidance may result in the most adequate policies in terms of increasing the engagement and game performance of users, but a large-scale user study is needed to verify the validity of that observation.

Real-Time Optimal Synthetic Inversion Recovery Image Selection (RT-OSIRIS) for Deep Brain Stimulation Targeting.

Deep brain stimulation (DBS) is a method of electrical neuromodulation used to treat a variety of neuropsychiatric conditions including essential tremor, Parkinson's disease, epilepsy, and obsessive-compulsive disorder. The procedure requires precise placement of electrodes such that the electrical contacts lie within or in close proximity to specific target nuclei and tracts located deep within the brain. DBS electrode trajectory planning has become increasingly dependent on direct targeting with the need for precise visualization of targets. MRI is the primary tool for direct visualization, and this has led to the development of numerous sequences to aid in visualization of different targets. Synthetic inversion recovery images, specified by an inversion time parameter, can be generated from T1 relaxation maps, and this represents a promising method for modifying the contrast of deep brain structures to accentuate target areas using a single acquisition. However, there is currently no accessible method for dynamically adjusting the inversion time parameter and observing the effects in real-time in order to choose the optimal value. In this work, we examine three different approaches to implementing an application for real-time optimal synthetic inversion recovery image selection and evaluate them based on their ability to display continually-updated synthetic inversion recovery images as the user modifies the inversion time parameter. These methods include continuously computing the inversion recovery equation at each voxel in the image volume, limiting the computation only to the voxels of the orthogonal slices currently displayed on screen, or using a series of lookup tables with precomputed solutions to the inversion recovery equation. We find the latter implementation provides for the quickest display updates both when modifying the inversion time and when scrolling through the image. We introduce a publicly available cross-platform application built around this conclusion. We also briefly discuss other details of the implementations and considerations for extensions to other use cases.

Evaluating the User Experience of a Smartphone-Delivered Sexual Health Promotion Program for Older Adults in the Netherlands: Single-Arm Pilot Study.

BACKGROUND: Sexual health is an important component of quality of life in older adults. However, older adults often face barriers to attaining a fulfilling sexual life because of issues such as stigma, lack of information, or difficult access to adequate support. OBJECTIVE: We aimed to evaluate the user experience of a self-guided, smartphone-delivered program to promote sexual health among older adults. METHODS: The mobile app was made available to community-dwelling older adults in the Netherlands, who freely used the app for 8 weeks. User experience and its respective components were assessed using self-developed questionnaires, the System Usability Scale, and semistructured interviews. Quantitative and qualitative data were descriptively and thematically analyzed, respectively. RESULTS: In total, 15 participants (mean age 71.7, SD 9.5 years) completed the trial. Participants showed a neutral to positive stance regarding the mobile app's usefulness and ease of use. Usability was assessed as "Ok/Fair." The participants felt confident about using the mobile app. To increase user experience, participants offered suggestions to improve content and interaction, including access to specialized sexual health services. CONCLUSIONS: The sexual health promotion program delivered through a smartphone in a self-guided mode was usable. Participants' perception is that improvements to user experience, namely in content and interaction, as well as connection to external services, will likely improve usefulness and acceptance.

Analysis of standard unit carbon emission and cost assessment of the changing building envelope over material production phase.

It is undeniable that the material production stage is crucial to the whole life cycle of structures. This study proposes the window-to-envelope ratio (WER) based on standard units to determine the inherent relationship between changes in door and window areas and carbon emissions, presuming six distinct types of engineering practices for various buildings are selected. It was concluded that larger door and window areas would result in more embodied carbon emissions. Additionally, as the size of windows and doors increases, the costs and embodied carbon of prefabricated and cast-in-place construction become more comparable. According to the analysis, when the building scale is larger and the door and window opening area is also larger, prefabrication has more potential for saving carbon than cast-in-place building, but with a cost of approximately 10-20% higher. Considering the perspective of consumers, producers, and markets, this study revealed a costing assessment methodology based on standard units for prefabricated structures. In this methodology, producers choose and create various residential layouts based on the distinctive requirements of consumers, while tracking the trends in carbon emissions and production costs. This assessment method tries to create a favorable atmosphere for moral market activity and offers an acceptable solution for the trade-off between environmental and economic factors throughout the material production phase of the building.

Development of a Management App for Postviral Fibromyalgia-Like Symptoms: Patient Preference-Guided Approach.

BACKGROUND: Persistent fibromyalgia-like symptoms have been increasingly reported following viral infections, including SARS-CoV-2. About 30% of patients with post-COVID-19 syndrome fulfill the fibromyalgia criteria. This complex condition presents significant challenges in terms of self-management. Digital health interventions offer a viable means to assist patients in managing their health conditions. However, the challenge of ensuring their widespread adoption and adherence persists. This study responds to this need by developing a patient-centered digital health management app, incorporating patient preferences to enhance usability and effectiveness, ultimately aiming to improve patient outcomes and quality of life. OBJECTIVE: This research aims to develop a digital health self-management app specifically for patients experiencing postviral fibromyalgia-like symptoms. By prioritizing patient preferences and engagement through the app's design and functionality, the study intends to facilitate better self-management practices and improve adherence. METHODS: Using an exploratory study design, the research used patient preference surveys and usability testing as primary tools to inform the development process of the digital health solution. We gathered and analyzed patients' expectations regarding design features, content, and usability to steer the iterative app development. RESULTS: The study uncovered crucial insights from patient surveys and usability testing, which influenced the app's design and functionality. Key findings included a preference for a symptom list over an automated chatbot, a desire to report on a moderate range of symptoms and activities, and the importance of an intuitive onboarding process. While usability testing identified some challenges in the onboarding process, it also confirmed the importance of aligning the app with patient needs to enhance engagement and satisfaction. CONCLUSIONS: Incorporating patient feedback has been a significant factor in the development of the digital health app. Challenges encountered with user onboarding during usability testing have highlighted the importance of this process for user adoption. The study acknowledges the role of patient input in developing digital health technologies and suggests further research to improve onboarding procedures, aiming to enhance patient engagement and their ability to manage digital health resources effectively. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/32193.

Incorporating Cardiovascular Risk Assessment into Adolescent Reproductive Health and Primary Care Visits.

STUDY OBJECTIVE: This study aimed to evaluate the usability and feasibility of incorporating a cardiovascular risk assessment tool into adolescent reproductive health and primary care visits. METHODS: We recruited 60 young women ages 13-21 years to complete the HerHeart web-tool in two adolescent clinics in Atlanta, GA. Participants rated the tool's usability via the Website Analysis and Measurement Inventory (WAMMI, range 0-95) and their perceived 10-year and lifetime risk of cardiovascular disease (CVD) on a visual analog scale (range 0-10). Participants' perceived risk, blood pressure, and body mass index were measured at baseline and three months after enrollment. Healthcare providers (HCP, n=5) completed the WAMMI to determine the usability and feasibility of incorporating the HerHeart tool into clinical practice. RESULTS: Adolescent participants and HCPs rated the tool's usability highly on the WAMMI with a median of 79 (IQR 65, 84) and 76 (IQR 71, 84). At the baseline visit, participants' median perceived 10-year risk of a heart attack was 1 (IQR 0, 3), and perceived lifetime risk was 2 (IQR 0, 4). Immediately after engaging with the tool, participants' median perceived 10-year risk was 2 (IQR 1, 4.3), and perceived lifetime risk was 3 (IQR 1.8, 6). Thirty-one participants chose to set a behavior change goal, and 12 participants returned for follow-up. Clinical metrics were similar at the baseline and follow-up visits. CONCLUSION: HerHeart is acceptable to young women and demonstrates potential for changing risk perception and improving health habits to reduce risk of CVD. Future research should focus on improving retention in studies to promote cardiovascular health within reproductive health clinics.