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1.
Psychiatr Danub ; 32(1): 25-31, 2020.
Article in English | MEDLINE | ID: covidwho-2100748

ABSTRACT

Deep emotional traumas in societies overwhelmed by large-scale human disasters, like, global pandemic diseases, natural disasters, man-made tragedies, war conflicts, social crises, etc., can cause massive stress-related disorders. Motivated by the ongoing global coronavirus pandemic, the article provides an overview of scientific evidence regarding adverse impact of diverse human disasters on mental health in afflicted groups and societies. Following this broader context, psychosocial impact of COVID-19 as a specific global human disaster is presented, with an emphasis on disturbing mental health aspects of the ongoing pandemic. Limited resources of mental health services in a number of countries around the world are illustrated, which will be further stretched by the forthcoming increase in demand for mental health services due to the global COVID-19 pandemic. Mental health challenges are particularly important for the Republic of Croatia in the current situation, due to disturbing stress of the 2020 Zagreb earthquake and the high pre-pandemic prevalence of chronic Homeland-War-related posttraumatic stress disorders. Comprehensive approach based on digital psychiatry is proposed to address the lack of access to psychiatric services, which includes artificial intelligence, telepsychiatry and an array of new technologies, like internet-based computer-aided mental health tools and services. These tools and means should be utilized as an important part of the whole package of measures to mitigate negative mental health effects of the global coronavirus pandemic. Our scientific and engineering experiences in the design and development of digital tools and means in mitigation of stress-related disorders and assessment of stress resilience are presented. Croatian initiative on enhancement of interdisciplinary research of psychiatrists, psychologists and computer scientists on the national and EU level is important in addressing pressing mental health concerns related to the ongoing pandemic and similar human disasters.


Subject(s)
Coronavirus Infections/psychology , Disasters , Mental Health Services , Mental Health , Pneumonia, Viral/psychology , Psychiatry , Telemedicine , Artificial Intelligence , Betacoronavirus , COVID-19 , Croatia , Humans , Internet , Pandemics , Psychiatry/trends , SARS-CoV-2 , Telemedicine/trends , User-Computer Interface
2.
Neurosurg Focus ; 53(2): E2, 2022 08.
Article in English | MEDLINE | ID: covidwho-2022558

ABSTRACT

OBJECTIVE: The longer learning curve and smaller margin of error make nontraditional, or "out of operating room" simulation training, essential in neurosurgery. In this study, the authors propose an evaluation system for residents combining both task-based and procedure-based exercises and also present the perception of residents regarding its utility. METHODS: Residents were evaluated using a combination of task-based and virtual reality (VR)-based exercises. The results were analyzed in terms of the seniority of the residents as well as their laboratory credits. Questionnaire-based feedback was sought from the residents regarding the utility of this evaluation system incorporating the VR-based exercises. RESULTS: A total of 35 residents were included in this study and were divided into 3 groups according to seniority. There were 11 residents in groups 1 and 3 and 13 residents in group 2. On the overall assessment of microsuturing skills including both 4-0 and 10-0 microsuturing, the suturing skills of groups 2 and 3 were observed to be better than those of group 1 (p = 0.0014). Additionally, it was found that microsuturing scores improved significantly with the increasing laboratory credits (R2 = 0.72, p < 0.001), and this was found to be the most significant for group 1 residents (R2 = 0.85, p < 0.001). Group 3 residents performed significantly better than the other two groups in both straight (p = 0.02) and diagonal (p = 0.042) ring transfer tasks, but there was no significant difference between group 1 and group 2 residents (p = 0.35). Endoscopic evaluation points were also found to be positively correlated with previous laboratory training (p = 0.002); however, for the individual seniority groups, the correlation failed to reach statistical significance. The 3 seniority groups performed similarly in the cranial and spinal VR modules. Group 3 residents showed significant disagreement with the utility of the VR platform for improving surgical dexterity (p = 0.027) and improving the understanding of surgical procedures (p = 0.034). Similarly, there was greater disagreement for VR-based evaluation to identify target areas of improvement among the senior residents (groups 2 and 3), but it did not reach statistical significance (p = 0.194). CONCLUSIONS: The combination of task- and procedure-based assessment of trainees using physical and VR simulation models can supplement the existing neurosurgery curriculum. The currently available VR-based simulations are useful in the early years of training, but they need significant improvement to offer beneficial learning opportunities to senior trainees.


Subject(s)
Internship and Residency , Neurosurgery , Clinical Competence , Curriculum , Humans , Learning Curve , Neurosurgery/education , User-Computer Interface
3.
Sci Rep ; 12(1): 14575, 2022 08 26.
Article in English | MEDLINE | ID: covidwho-2008311

ABSTRACT

Public access automated external defibrillators (AEDs) represent emergency medical devices that may be used by untrained lay-persons in a life-critical event. As such their usability must be confirmed through simulation testing. In 2020 the novel coronavirus caused a global pandemic. In order to reduce the spread of the virus, many restrictions such as social distancing and travel bans were enforced. Usability testing of AEDs is typically conducted in-person, but due to these restrictions, other usability solutions must be investigated. Two studies were conducted, each with 18 participants: (1) an in-person usability study of an AED conducted in an office space, and (2) a synchronous remote usability study of the same AED conducted using video conferencing software. Key metrics associated with AED use, such as time to turn on, time to place pads and time to deliver a shock, were assessed in both studies. There was no difference in time taken to turn the AED on in the in-person study compared to the remote study, but the time to place electrode pads and to deliver a shock were significantly lower in the in-person study than in the remote study. Overall, the results of this study indicate that remote user testing of public access defibrillators may be appropriate in formative usability studies for determining understanding of the user interface.


Subject(s)
COVID-19 , Cardiopulmonary Resuscitation , Defibrillators/classification , Out-of-Hospital Cardiac Arrest/therapy , Physical Distancing , Cardiopulmonary Resuscitation/methods , Cardiopulmonary Resuscitation/standards , Defibrillators/standards , Defibrillators/statistics & numerical data , Humans , Pandemics , Time Factors , User-Centered Design , User-Computer Interface
4.
J Laryngol Otol ; 136(9): 785-787, 2022 09.
Article in English | MEDLINE | ID: covidwho-1991452
6.
IEEE Trans Neural Syst Rehabil Eng ; 30: 1652-1663, 2022.
Article in English | MEDLINE | ID: covidwho-1937854

ABSTRACT

The rejection rates of upper-limb prosthetic devices in adults are high, currently averaging 26% and 23% for body-powered and electric devices, respectively. While many factors influence acceptance, prosthesis training methods relying on novel virtual reality systems have been cited as a critical factor capable of increasing the likelihood of long-term, full-time use. Despite that, these implementations have not yet garnered widespread traction in the clinical setting, and their use remains immaterial. This review aims to explore the reasons behind this situation by identifying trends in existing research that seek to advance Extended Reality "X-Reality" systems for the sake of upper-limb prosthesis rehabilitation and, secondly, analyzing barriers and presenting potential pathways to deployment for successful adoption in the future. The search yielded 42 research papers that were divided into two categories. The first category included articles that focused on the technical aspect of virtual prosthesis training. Articles in the second category utilize user evaluation procedures to ensure applicability in a clinical environment. The review showed that 75% of articles that conducted whole system testing experimented with non-immersive virtual systems. Furthermore, there is a shortage of experiments performed with amputee subjects. From the large-scale studies analyzed, 71% of those recruited solely non-disabled participants. This paper shows that X-Reality technologies for prosthesis rehabilitation of upper-limb amputees carry significant benefits. Nevertheless, much still must be done so that the technology reaches widespread clinical use.


Subject(s)
Amputees , Artificial Limbs , Adult , Amputees/rehabilitation , Humans , Prosthesis Implantation , Upper Extremity , User-Computer Interface
7.
Stud Health Technol Inform ; 290: 1136-1137, 2022 Jun 06.
Article in English | MEDLINE | ID: covidwho-1933599

ABSTRACT

In 2020, a pandemic forced the entire world to adapt to a new scenario. The objective of this study was to know how Health Information Systems were adapted driven by the pandemic of COVID. 12 CIOS of healthcare organizations were interviewed and the interviews were classified according to the dimensions of a sociotechnical model: Infrastructure, Clinical Content, Human Computer Interface, People, Workflow and Communication, Organizational Characteristics and Internal Policies, Regulations, and Measurement and Monitoring. Adaptation to the Pandemic involved social, organizational and cultural rather than merely technical aspects in private organizations with mature and stable Health Information Systems.


Subject(s)
COVID-19 , Health Information Systems , Humans , Pandemics , User-Computer Interface , Workflow
8.
Stud Health Technol Inform ; 290: 424-427, 2022 Jun 06.
Article in English | MEDLINE | ID: covidwho-1933563

ABSTRACT

Usability testing has historically been an in-person activity where test participants and evaluation researchers are co-located. Recruiting participants into usability studies can be a challenging endeavor especially when potential participants are concerned about time commitments and social distancing. The global COVID-19 pandemic has driven the development of remote usability testing methods. In this paper, we describe remote usability testing as it evolved during a pre-pandemic research study. We adapted our in-person usability evaluation methodology for a commercially available mHealth app to a remote usability testing methodology to accommodate potential participants during a more convenient participant-identified time. In doing so we met the needs, preferences, and availability of our participants and maintained research progress. Adapting to patient-centered needs through remote usability testing has the potential to facilitate continued research and engage potential participants due to its convenience, flexibility, and decrease constraints presented by geographic limits.


Subject(s)
COVID-19 , Mobile Applications , COVID-19/epidemiology , Humans , Pandemics , User-Centered Design , User-Computer Interface
9.
Stud Health Technol Inform ; 295: 285-288, 2022 Jun 29.
Article in English | MEDLINE | ID: covidwho-1924034

ABSTRACT

Telehealth services were made available in the Kingdom of Saudi Arabia through a number of different mobile applications, one of which is the Sehhaty application. Studies are needed to evaluate how consumers are perceiving these services, during the COVID-19 pandemic. This study aims to measure consumers' satisfaction with telehealth services provided by the Sehhaty application and to compare the results to other countries using similar telehealth services. The telehealth usability questionnaire (TUQ) tool was used to construct an online survey to gather consumers' usability assessment and measure satisfaction. The study provides strong evidence that Sehhaty application has a high acceptance rate among users with 76.36% overall satisfaction. Although, 44.34% of participants liked using Sehhaty application, a total of 68.87% participants prefers in-person visits. As a result, more studies need to be conducted to identify factors affecting satisfaction levels for Sehhaty telehealth solutions by the public.


Subject(s)
COVID-19 , Telemedicine , COVID-19/epidemiology , Humans , Pandemics , Saudi Arabia , Telemedicine/methods , User-Computer Interface
10.
Sci Rep ; 12(1): 3797, 2022 03 08.
Article in English | MEDLINE | ID: covidwho-1908239

ABSTRACT

Infectious threats, like the COVID-19 pandemic, hinder maintenance of a productive and healthy workforce. If subtle physiological changes precede overt illness, then proactive isolation and testing can reduce labor force impacts. This study hypothesized that an early infection warning service based on wearable physiological monitoring and predictive models created with machine learning could be developed and deployed. We developed a prototype tool, first deployed June 23, 2020, that delivered continuously updated scores of infection risk for SARS-CoV-2 through April 8, 2021. Data were acquired from 9381 United States Department of Defense (US DoD) personnel wearing Garmin and Oura devices, totaling 599,174 user-days of service and 201 million hours of data. There were 491 COVID-19 positive cases. A predictive algorithm identified infection before diagnostic testing with an AUC of 0.82. Barriers to implementation included adequate data capture (at least 48% data was needed) and delays in data transmission. We observe increased risk scores as early as 6 days prior to diagnostic testing (2.3 days average). This study showed feasibility of a real-time risk prediction score to minimize workforce impacts of infection.


Subject(s)
Algorithms , COVID-19/diagnosis , Monitoring, Physiologic/methods , Area Under Curve , COVID-19/virology , Humans , Military Personnel , Monitoring, Physiologic/instrumentation , ROC Curve , SARS-CoV-2/isolation & purification , User-Computer Interface , Wearable Electronic Devices
11.
Lancet ; 399(10344): 2336, 2022 06 25.
Article in English | MEDLINE | ID: covidwho-1900298
12.
Br J Nurs ; 31(8): 412, 2022 04 21.
Article in English | MEDLINE | ID: covidwho-1835944
13.
Int Psychogeriatr ; 34(2): 97-99, 2022 02.
Article in English | MEDLINE | ID: covidwho-1778558
14.
Front Public Health ; 9: 748307, 2021.
Article in English | MEDLINE | ID: covidwho-1775924

ABSTRACT

End-user involvement constitutes an essential goal during the development of innovative solution, not only for the evaluation, but also in codesign, following a user-centered strategy. Indeed, it is a great asset of research to base the work in a user-centered approach, because it allows to build a platform that will respond to the real needs of users. The aims of this work are to present the methodology adopted to involve end-users (i.e., neurological patients, healthy elderly, and health professionals) in the evaluation of a novel virtual coaching system based on the personalized clinical pathways and to present the results obtained from these preliminary activities. Specific activities involving end-users were planned along the development phases and are referred to as participatory design. The user experience of participatory design is constituted by the two different phases: the "end-user's perspective" phase where the user involvement in experiential activities is from an observational point of view, whereas the "field study" phase is the direct participation in these activities. Evaluation tools (i.e., scales, questionnaires, and interviews) were planned to assess different aspects of the system. Thirty patients [14 with poststroke condition and 16 with Parkinson's disease (PD)], 13 healthy elderly, and six health professionals were enrolled from two clinical centers during the two phases of participatory design. Results from "end-user's perspective" phase showed globally a positive preliminary perception of the service. Overall, a positive evaluation (i.e., UEQ median score > 1) was obtained for each domain of the scale in both groups of patients and healthy subjects. The evaluation of the vCare system during the "field study" phase was assessed as excellent (>80 points) from the point of view of both patients and health professionals. According to the majority of patients, the rehabilitation service through the solution was reported to be interesting, engaging, entertaining, challenging and useful for improving impaired motor functions, and making patients aware of their cognitive abilities. Once refined and fine-tuned in the aspects highlighted in the this work, the system will be clinically tested at user's home to measure the real impact of the rehabilitative coaching services.


Subject(s)
Mentoring , Aged , Humans , Motivation , Surveys and Questionnaires , User-Computer Interface
15.
Brief Bioinform ; 23(2)2022 03 10.
Article in English | MEDLINE | ID: covidwho-1704326

ABSTRACT

Protein lysine crotonylation (Kcr) is an important type of posttranslational modification that is associated with a wide range of biological processes. The identification of Kcr sites is critical to better understanding their functional mechanisms. However, the existing experimental techniques for detecting Kcr sites are cost-ineffective, to a great need for new computational methods to address this problem. We here describe Adapt-Kcr, an advanced deep learning model that utilizes adaptive embedding and is based on a convolutional neural network together with a bidirectional long short-term memory network and attention architecture. On the independent testing set, Adapt-Kcr outperformed the current state-of-the-art Kcr prediction model, with an improvement of 3.2% in accuracy and 1.9% in the area under the receiver operating characteristic curve. Compared to other Kcr models, Adapt-Kcr additionally had a more robust ability to distinguish between crotonylation and other lysine modifications. Another model (Adapt-ST) was trained to predict phosphorylation sites in SARS-CoV-2, and outperformed the equivalent state-of-the-art phosphorylation site prediction model. These results indicate that self-adaptive embedding features perform better than handcrafted features in capturing discriminative information; when used in attention architecture, this could be an effective way of identifying protein Kcr sites. Together, our Adapt framework (including learning embedding features and attention architecture) has a strong potential for prediction of other protein posttranslational modification sites.


Subject(s)
Computational Biology , Deep Learning , Lysine/metabolism , Protein Processing, Post-Translational , Software , Algorithms , Benchmarking , Computational Biology/methods , Computational Biology/standards , Databases, Factual , Neural Networks, Computer , Phosphorylation , ROC Curve , Reproducibility of Results , User-Computer Interface
16.
Acta Crystallogr D Struct Biol ; 78(Pt 2): 152-161, 2022 Feb 01.
Article in English | MEDLINE | ID: covidwho-1684950

ABSTRACT

Recently, there has been a dramatic improvement in the quality and quantity of data derived using cryogenic electron microscopy (cryo-EM). This is also associated with a large increase in the number of atomic models built. Although the best resolutions that are achievable are improving, often the local resolution is variable, and a significant majority of data are still resolved at resolutions worse than 3 Å. Model building and refinement is often challenging at these resolutions, and hence atomic model validation becomes even more crucial to identify less reliable regions of the model. Here, a graphical user interface for atomic model validation, implemented in the CCP-EM software suite, is presented. It is aimed to develop this into a platform where users can access multiple complementary validation metrics that work across a range of resolutions and obtain a summary of evaluations. Based on the validation estimates from atomic models associated with cryo-EM structures from SARS-CoV-2, it was observed that models typically favor adopting the most common conformations over fitting the observations when compared with the model agreement with data. At low resolutions, the stereochemical quality may be favored over data fit, but care should be taken to ensure that the model agrees with the data in terms of resolvable features. It is demonstrated that further re-refinement can lead to improvement of the agreement with data without the loss of geometric quality. This also highlights the need for improved resolution-dependent weight optimization in model refinement and an effective test for overfitting that would help to guide the refinement process.


Subject(s)
Cryoelectron Microscopy/methods , Software Validation , Software , COVID-19 , Image Processing, Computer-Assisted , Models, Molecular , Reproducibility of Results , User-Computer Interface
17.
Am J Med Genet A ; 188(4): 1142-1148, 2022 04.
Article in English | MEDLINE | ID: covidwho-1593959

ABSTRACT

We studied if clinicians could gain sufficient working knowledge of a computer-assisted diagnostic decision support system (DDSS) (SimulConsult), to make differential diagnoses (DDx) of genetic disorders. We hypothesized that virtual training could be convenient, asynchronous, and effective in teaching clinicians how to use a DDSS. We determined the efficacy of virtual, asynchronous teaching for clinicians to gain working knowledge to make computer-assisted DDx. Our study consisted of three surveys (Baseline, Training, and After Use) and a series of case problems sent to clinicians at Vanderbilt University Medical Center. All participants were able to generate computer-assisted DDx that achieved passing scores of the case problems. Between 75% and 92% agreed/completely agreed the DDSS was useful to their work and for clinical decision support and was easy to use. Participants' use of the DDSS resulted in statistically significant time savings in key tasks and in total time spent on clinical tasks. Our results indicate that virtual, asynchronous teaching can be an effective format to gain a working knowledge of a DDSS, and its clinical use could result in significant time savings across multiple tasks as well as facilitate synergistic interaction between clinicians and lab specialists. This approach is especially pertinent and offers value amid the COVID-19 pandemic.


Subject(s)
Diagnosis, Computer-Assisted , Genetic Diseases, Inborn/diagnosis , Genetic Diseases, Inborn/genetics , Teaching , User-Computer Interface , Decision Support Systems, Clinical , Diagnosis, Computer-Assisted/methods , Education, Medical , Humans , Physicians , Surveys and Questionnaires
19.
Medicine (Baltimore) ; 100(50): e27844, 2021 Dec 17.
Article in English | MEDLINE | ID: covidwho-1583963

ABSTRACT

INTRODUCTION: Due to the current COVID-19 pandemic, surgical training has become increasingly challenging due to required social distancing. Therefore, the use of virtual reality (VR)-simulation could be a helpful tool for imparting surgical skills, especially in minimally invasive environments. Visual spatial ability (VSA) might influence the learning curve for laparoscopic surgical skills. However, little is known about the influence of VSA for surgical novices on VR-simulator training regarding the complexity of different tasks over a long-term training period. Our study evaluated prior VSA and VSA development in surgical trainees during VR-simulator training, and its influence on surgical performance in simulator training. METHODS: In our single-center prospective two-arm randomized trial, VSA was measured with a tube figure test before curriculum training. After 1:1 randomization, the training group (TG) participated in the entire curriculum training consisting of 48 different VR-simulator tasks with varying difficulty over a continuous nine-day training session. The control group (CG) performed two of these tasks on day 1 and 9. Correlation and regression analyses were used to assess the influence of VSA on VR-related surgical skills and to measure procedural abilities. RESULTS: Sixty students (33 women) were included. Significant improvements in the TG in surgical performance and faster completion times were observed from days 1 to 9 for the scope orientation 30° right-handed (SOR), and cholecystectomy dissection tasks after the structured 9-day training program. After training, the TG with pre-existing low VSA scores achieved performance levels similar to those with pre-existing high VSA scores for the two VR simulator tasks. Significant correlations between VSA and surgical performance on complex laparoscopic camera navigation SOR tasks were found before training. CONCLUSIONS: Our study revealed that that all trainees improved their surgical skills irrespective of previous VSA during structured VR simulator training. An increase in VSA resulted in improvements in surgical performance and training progress, which was more distinct in complex simulator tasks. Further, we demonstrated a positive relationship between VSA and surgical performance of the TG, especially at the beginning of training. Our results identified pre-existing levels of VSA as a predictor of surgical performance.


Subject(s)
Clinical Competence , Laparoscopy , Simulation Training , Spatial Navigation , Virtual Reality , COVID-19 , Female , Humans , Laparoscopy/education , Pandemics , Prospective Studies , User-Computer Interface
20.
Comput Math Methods Med ; 2021: 1546343, 2021.
Article in English | MEDLINE | ID: covidwho-1574507

ABSTRACT

As the COVID-19 pandemic continues, the need for a better health care facility is highlighted more than ever. Besides physical health, mental health conditions have become a significant concern. Unfortunately, there are few opportunities for people to receive mental health care. There are inadequate facilities for seeking mental health support even in big cities, let alone remote areas. This paper presents the structure and implementation procedures for a mental health support system combining technology and professionals. The system is a web platform where mental health seekers can register and use functionalities like NLP-based chatbot for personality assessment, chatting with like-minded people, and one-to-one video conferencing with a mental health professional. The video calling feature of the system has emotion detection capabilities using computer vision. The system also includes downloadable prescription facilities and a payment gateway for secure transactions. From a technological aspect, the conversational NLP-based chatbot and computer vision-powered video calling are the system's most important features. The system has a documentation facility to analyze the mental health condition over time. The web platform is built using React.js for the frontend and Express.js for the backend. MongoDB is used as the database of the platform. The NLP chatbot is built on a three-layered deep neural network model that is programmed in the Python language and uses the NLTK, TensorFlow, and Keras sequential API. Video conference is one of the most important features of the platform. To create the video calling feature, Express.js, Socket.io, and Socket.io-client have been used. The emotion detection feature is implemented on video conferences using computer vision, Haar Cascade, and TensorFlow. All the implemented features are tested and work fine. The targeted users for the platform are teenagers, youth, and the middle-aged population. Mental health-seeking is still considered taboo in some societies today. Apart from basic established facilities, this social dilemma of undergoing treatment for mental health is causing severe damage to individuals. A solution to this problem can be a remote platform for mental health support. With this goal in mind, this system is designed to provide mental health support to people remotely from anywhere worldwide.


Subject(s)
Mental Health , Software , Telemedicine , Humans , Internet , Natural Language Processing , User-Computer Interface , Videoconferencing
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