Virtual reality-based interventions for patients with paranoia:A systematic review

Background and objective: Paranoia is an important psychiatric symptom with a remarkable effect on daily life. Virtual reality (VR)-based treatments are influential and safe for patients with paranoia. This study aimed to evaluate the effectiveness, and define the clinical and technical characteristics of available VR strategies for the treatment of patients with paranoia. Materials and methods: Studies published up to 25/11/2021 reporting VR-based interventions for the treatment of patients with paranoia were reviewed in five databases, including PubMed, Embase, Web of Science, PsycINFO, and Scopus. Results: Out of 302 initial search results, eight were included in the present study based on the inclusion criteria. Six studies were randomized clinical trials with the interventions in the experimental group being based on VR, compared to routine interventions as controls. Two were before-after studies. The most commonly used hardware and software were head-mounted display and Unity3D, respectively. Interventions had a range of 1-16 sessions with follow-up durations of 0-6 months. All investigations showed positive results in the main target, including improved social participation, reduced level of anxiety, as well as diminished suspicious ideas and paranoid symptoms. Conclusions: Our findings demonstrated that VR-based interventions are effective treatments. Although the use of VR technology is limited for a variety of reasons, such as cost, it improves symptoms in patients with paranoia

Using a Question Answering System to Enhance Knowledge and Improve the Exchange of Information among Physicians

Due to limited time, physicians often find it challenging to find the exact answers to their questions among search engine results; however, question and answer (Q&A) systems can facilitate more rapidly identify accurate solutions. This study aims to develop and evaluate a Q&A system for physicians at Tabriz University of Medical Sciences. Four clinical and informatics experts and the two health information managers agreed on 19 features and themes throughout two focus group meetings. Subsequently, a system was developed on a MySQL database using the PHP web development language and then uploaded to the web. Finally, the system was opened up to 40 users and, over three months, evaluated using a community evaluation questionnaire and the six-dimension Users’ Experience Questionnaire. The focus group results in determining the features of the Q&A system consisted of 19 requirements. The average attractiveness, perspicuity, efficiency, dependability, stimulation, and novelty were equal to 1.76, 1.625, 1.9, 1.425, 1.475, and 1.375, respectively. The Q&A system improved the tasks such as share of knowledge, transfer of information, social partnership, and cooperation among users. The physicians were able to obtain the information they required through contact with their co-practitioners over the system.https://dorl.net/dor/20.1001.1.20088302.2021.19.2.14.

National Minimum Data Set for Antimicrobial Resistance Management: Toward Global Surveillance System

Background: Success of infection treatment depends on the availability of accurate, reliable, and comprehensive data, information, and knowledge at the point of therapeutic decision-making. The identification of a national minimum data set will support the development and implementation of an effective surveillance system. The goal of this study was to develop a national antimicrobial resistance surveillance minimum data set. Methods: In this cross-sectional and descriptive study, data were collected from selected pioneering countries and organizations which have national or international antimicrobial resistance surveillance systems. A minimum data set checklist was extracted and validated. The ultimate data elements of the minimum data set were determined by applying the Delphi technique. Results: Through the Delphi technique, we obtained 80 data elements in 8 axes. The resistance data categories comprised basic, clinical, electronic reporting, infection control, microbiology, pharmacy, World Health Organization-derived, and expert-recommended data. Relevance coding was extracted based on the Iranian electronic health record coding system. Conclusion: This study provides a set of data elements and a schematic framework for the implementation of an antimicrobial resistance surveillance system. A uniform minimum data set was created based on key informants’ opinions to cover essential needs in the early implementation of a global antimicrobial resistance surveillance system in Iran

Designing an Electronic Medical Record System of Infants in Hospitals of Tabriz University of Medical Sciences

Introduction: Developing an accurate and comprehensive electronic database which can capture and store adequate, accurate and timely data related to infants is an essential step. The aim of this study was to design an electronic medical record system for infants hospitalized in neonatal intensive care unit at the Hospitals of Tabriz University of Medical Sciences. Method: This was an applied-developmental study. At first, current status of a data recording process in hospitals was studied. Then data elements were determined and the new system was modeled. The proposed architecture is based on three-tier architecture. Services such as reporting and user access control levels were implemented. Design of the user interface layer was performed by using Asp.net framework and HTML. This system is available in private network of Tabriz University of Medical Sciences for authorized users since 2014. Results: In data access layer, the minimum data elements determined at the seven categories of information. To design a data model, 65 entities were defined with their attributes and relationships. In business layer, the key processes of the system were designed as system use cases. This system provides the real time and online data storage and retrieval for users at the point of care. Conclusion: The design and implementation of electronic medical records is an effective step in managing infant’s health data. Using the appropriate architecture and standard templates lead to enhanced efficient performance, function, and storage and retrieval of health data

Applications of virtual and augmented reality in infectious disease epidemics with a focus on the COVID-19 outbreak

The pandemics of major infectious diseases often cause public health, economic, and social problems. Virtual reality (VR) and augmented reality (AR), as two novel technologies, have been used in many fields for emergency management of disasters. The objective of this paper was to review VR and AR applications in the emergency management of infectious outbreaks with an emphasis on the COVID-19 outbreak. A search was conducted in MEDLINE (PubMed), Embase, IEEE, Cochrane Library, Google Scholar, and related websites for papers published up to May 2, 2020. The VR technology has been used for preventing or responding to infections by simulating human behaviors, infection transmission, and pathogen structure as a means for improving skills management and safety protection. Telehealth, telecommunication, and drug discovery have been among the other applications of VR during this pandemic. Moreover, AR has also been used in various industries, including healthcare, marketing, universities, and schools. Providing high-resolution audio and video communication, facilitating remote collaboration, and allowing the visualization of invisible concepts are some of the advantages of using this technology. However, VR has been used more frequently than AR in the emergency management of previous infectious diseases with a greater focus on education and training. The potential applications of these technologies for COVID-19 can be categorized into four groups, i.e., 1) entertainment, 2) clinical context, 3) business and industry, and 4) education and training. The results of this study indicate that VR and AR have the potential to be used for emergency management of infectious diseases. Further research into employing these technologies will have a substantial impact on mitigating the destructive effects of infectious diseases. Making use of all the potential applications of these technologies should be considered for the emergency management of the current pandemic and mitigating its negative impacts

The effect of virtual reality therapy and counseling on students' public speaking anxiety

Abstract Background and Aims One of the barriers to effective communication between speaker and listeners is public speaking anxiety (PSA). Over recent years, PSA has become common among students as the most widespread social anxiety (SA). Virtual reality (VR) and counseling therapy help reduce PSA. Therefore, the present study aimed to investigate the effect of VR therapy and counseling on students' PSA and SA. Methods This quasi‐experimental study was conducted on 30 students at three levels of undergraduate, postgraduate, and PhD at Kerman University of Medical Sciences and Shiraz University of Medical Sciences (15 students in the intervention group and 15 in the control group). The intervention group observed four virtual classroom scenarios in a 30‐min session, and the control group attended a 90‐min group counseling session. Data were collected using by Personal Report of Public Speaking Anxiety, Liebowitz Social Anxiety Scale, and Igroup Presence Questionnaire. The data analysis was done using SPSS version 21. Descriptive analysis (frequency and percentage, mean, standard deviation, and quartiles) and analytical tests (paired t‐test and independent t‐test) were used to analyze the data. Results The results showed that VR and counseling did not affect SA scores and statistical differences before and after the intervention were not statistically significant. However, VR and counseling reduced PSA. The mean of IPQ/IGP (physical presence) was 63.73. The participants' SA means (93.76) were higher than the mean PSA (73.4). Conclusions VR and counseling did not affect students' SA, but they reduced PSA. If the intervention duration in future studies are longer, the effect of VR and counseling on reducing SA is likely to become more apparent

Effectiveness of virtual reality-based exercise therapy in rehabilitation: A scoping review

Background: When it comes to rehabilitation following many injuries and disabilities, exercise therapy is a long, arduous, and tedious process. Therefore, there is a need to employ new methods to increase the frequency, duration, and intensity of the exercises, and to boost motivation and satisfaction of the patients in a way that they can better perform the exercises. In this regard, virtual reality (VR) is an emerging technology that can be an effective tool in mitigating therapeutic challenges. Objectives: The main objective of the current study was to evaluate the effectiveness of VR-based exercise therapy to highlight areas for future studies in rehabilitation. Methods: The scoping review methodology was used to comprehensively search for and identify related papers in MEDLINE (PubMed), Cochrane Database of Systematic Reviews, EMBASE, IEEE, and Web of Science, while grey literature was also searched. Studies that used VR for exercise therapy were included in the current review. Quality assessment was performed using the Physiotherapy Evidence Database. The consensus was reached following two reviewers’ independent inclusion screening, data extraction, and appraisal. Results: Among 2887 identified studies, 26 papers were eligible to be included in this review. The results showed the positive effects of VR-based exercise therapy in a variety of conditions or disorders. With regard to treatment objectives, VR-based exercise therapy has been more commonly considered for the improvement of pain (41%), functional ability (31%), and muscular strength (24%). According to the findings, compared to other VR devices, Nintendo Wii and Kinect are 41% and 24% more common, respectively. Conclusions: This review provides evidence for the potential effectiveness of virtual reality-based exercise therapy for the improvement of rehabilitation outcomes. However, further higher-quality research is needed to confirm the observed positive effects

Simple and Efficient Measurement of the User Experience in Health Information Systems: A Persian Version

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CNN-Res: deep learning framework for segmentation of acute ischemic stroke lesions on multimodal MRI images

Abstract Background Accurate segmentation of stroke lesions on MRI images is very important for neurologists in the planning of post-stroke care. Segmentation helps clinicians to better diagnose and evaluation of any treatment risks. However, manual segmentation of brain lesions relies on the experience of neurologists and is also a very tedious and time-consuming process. So, in this study, we proposed a novel deep convolutional neural network (CNN-Res) that automatically performs the segmentation of ischemic stroke lesions from multimodal MRIs. Methods CNN-Res used a U-shaped structure, so the network has encryption and decryption paths. The residual units are embedded in the encoder path. In this model, to reduce gradient descent, the residual units were used, and to extract more complex information in images, multimodal MRI data were applied. In the link between the encryption and decryption subnets, the bottleneck strategy was used, which reduced the number of parameters and training time compared to similar research. Results CNN-Res was evaluated on two distinct datasets. First, it was examined on a dataset collected from the Neuroscience Center of Tabriz University of Medical Sciences, where the average Dice coefficient was equal to 85.43%. Then, to compare the efficiency and performance of the model with other similar works, CNN-Res was evaluated on the popular SPES 2015 competition dataset where the average Dice coefficient was 79.23%. Conclusion This study presented a new and accurate method for the segmentation of MRI medical images using a deep convolutional neural network called CNN-Res, which directly predicts segment maps from raw input pixels