Design and evaluation of a web-based electronic health record for amblyopia.

Introduction: Amblyopia, or lazy eye, is a type of visual impairment in which the eyesight is not complete, even with the use of glasses. For the treatment of this disease, accurate and continuous examinations are needed. Nowadays, patient-centered care, by relying on web-based electronic records for amblyopia, has the potential to reduce treatment costs, increase the quality of care, and improve the safety and effectiveness of treatment. Therefore, the purpose of this study is to design and evaluate an Electronic Health Record (EHR) for patients with amblyopia. Methods: The present study is applied developmental research. Using a Morgan table as a sampling tool, a straightforward random sampling technique selected 150 records from 1,500 records that were free of flaws. The design of the electronic version proceeded in a cascading manner so that after the design of each part, it was presented to the amblyopia experts, and if approved, the next part was designed. To design this EHR, the C# programming language and MySQL database were used. A system evaluation was performed by entering and recording patient information. For this purpose, the standard Questionnaire of User Interaction Satisfaction (QUIS), consisting of 18 questions, was used. Results: According to the amblyopia EHR data elements, the data of physician and patient, examinations, website members, and members' roles were determined. After defining the fields and classes that explain the tables, the EHR was designed. The usability evaluation of the system showed that the mean selection of very good and good options by the users of EHRs was over 90%, indicating the patients' acceptance of web-based EHRs. Conclusion: The design of an EHR for amblyopia is an effective step toward integrating and improving the information management of these patients. It will also enable the storage and retrieval of patients' information to reduce and facilitate the control of amblyopia complications.

Development and evaluation of a clinical decision support system for early diagnosis of acute appendicitis.

The most frequent reason for individuals experiencing abdominal discomfort to be referred to emergency departments of hospitals is acute appendicitis, and the most frequent emergency surgery performed is an appendectomy. The purpose of this study was to design and develop an intelligent clinical decision support system for the timely and accurate diagnosis of acute appendicitis. The number of participants which is equal to 181 was chosen as the sample size for developing and evaluating neural networks. The information was gathered from the medical files of patients who underwent appendicectomies at Shahid Modarres Hospital as well as from the findings of their appendix samples' pathological tests. The diagnostic outcomes were then ascertained by the development and comparison of a Multilayer Perceptron network (MLP) and a Support Vector Machine (SVM) system in the MATLAB environment. The SVM algorithm functioned as the central processing unit in the Clinical Decision Support System (CDSS) that was built. The intelligent appendicitis diagnostic system was subsequently developed utilizing the Java programming language. Technical evaluation and system usability testing were both done as part of the software evaluation process. Comparing the output of the optimized artificial neural network of the SVM with the pathology result showed that the network's sensitivity, specificity, and accuracy were 91.7%, 96.2%, and 95%, respectively, in diagnosing acute appendicitis. Based on the existing standards and the opinions of general surgeons, and also comparing the results with the diagnostic accuracy of general surgeons, findings indicated the proper functioning of the network for the diagnosis of acute appendicitis. The use of this system in medical centers is useful for purposes such as timely diagnosis and prevention of negative appendectomy, reducing patient hospital stays and treatment costs, and improving the patient referral system.

Smartphone-based application to control and prevent overweight and obesity in children: design and evaluation.

BACKGROUND: Obesity is a multifaceted condition that impacts individuals across various age, racial, and socioeconomic demographics, hence rendering them susceptible to a range of health complications and an increased risk of premature mortality. The frequency of obesity among adolescent females in Iran has exhibited an increase from 6 to 9%, while among boys, it has risen from 2 to 7%. Due to the increasing prevalence and advancements in technology, the primary objective of this study was to develop and evaluate a smartphone-based app that would serve as an educational tool for parents about the matter of childhood overweight and obesity. Additionally, the app aimed to enhance parents' capacity to effectively address and manage their children's weight-related concerns. METHODS: The design of the present study is of an applied-developmental type. In the first phase, the content of related smartphone-based app was determined based on the needs identified in similar studies and the findings of a researcher-made questionnaire. The versions of the app were designed in the android studio 3 programming environment, using the Java 8 programming language and SQLite database. Then, in order to evaluate the app's usability, ease of access, and different features, the standard usability evaluation questionnaire and the user satisfaction questionnaire (QUIS) were completed by the users. RESULTS: The developed app has five main sections: the main page, recommendation section (with eight parts), charts over the time, child psychology, and reminders for each user. The designed app was given to 20 people including nutritionists and parents with children under 18 years of age for conducting usability evaluation. According to the scores of participants about the usability evaluation of the app, it can be concluded that groups participating in the study could use the program, and they rated the app at a "good" level. Overall performance of the app, screen capabilities, terms and information of the program, learnability, and general features are scored higher than 7.5 out of 9. CONCLUSION: By using this app, people can become familiar with the causes and symptoms of weight imbalance and manage their weight as best as possible. This app can be considered as a model for designing and creating similar broader systems and programs for the prevention, management, treatment and care of diseases, which aim to help control diseases as much as possible and increase the quality of life and reduce complications for be patients.

Dos and don'ts in designing a computerized oral and lip squamous cell cancer registry.

BACKGROUND: In the last ten years, many countries have started to develop constructive systems for registering common diseases and cancers. In this research, we intended to determine and identify the minimum data set (MDS) required for the design of the oral and lip squamous cell cancer registration system in Iran. METHODS AND MATERIAL: At first, primary information elements related to disease registries were extracted using scientific papers published in reliable databases. After reviewing the books, related main guidelines, and 42 valid articles, the initial draft of a researcher-made questionnaire was compiled. To validate the questionnaire, two focus group meetings were held with 29 expert panel members. The final version of this questionnaire was prepared by extracting different questions and categories and receiving numerous pieces of feedback from specialists. Lastly, a final survey was conducted by the experts who were present at the previous stage. RESULTS: Out of 29 experts participating in the study, 17 (58.62%) were men and 12 (40.37%) were women. The age range of experts varies from 34 to 58 years. One hundred-fourteen items, which are divided into ten main parts, were considered the main information elements of the registry design. The main minimum data sets have pertained to the demographic and clinical information of the patient, information related to the consumed drugs, initial diagnostic evaluations of the patient, biopsy, tumor staging at the time of diagnosis, clinical characteristics of the tumor, surgery, histopathological characteristics of the tumor, pathologic stage classification, radiotherapy details, follow-up information, and disease registry capabilities. The distinctive characteristics of the oral and lip squamous cell cancer registry systems, such as the title of the disease registration programme, the population being studied, the geographic extent of the registration, its primary goals, the definition of the condition, the technique of diagnosis, and the kind of registration, are all included in a model. CONCLUSION: The benefits of designing and implementing disease registries can include timely access to medical records, registration of information related to patient care and follow-up of patients, the existence of standard forms and the existence of standard information elements, and the existence of an integrated information system at the country level.

Development and Evaluation of a Self-care Application Based on Herbal Medicine for Skin and Hair Diseases.

Background: Self-care applications are effective in the control and treatment of disease symptoms. Today, the mobile phone is used as one of the tools that can help us in this regard. The present study attempts to develop and evaluate a functional self-care mobile-phone application for patients with skin and hair problems using treatment protocols of herbal medicine. Materials and Methods: This study is a descriptive-applied type. At first, a questionnaire was prepared for data need assessment and also to determine the data items and required capabilities of the application. Based on the results, an application was designed using the Java programing language in the Android software environment. In the next step, the application was installed on the mobile phones of several specialists and patients, and the necessary corrections were made. Then, the final version of the application was evaluated. Results: The most critical data elements of the mobile application for skin and hair patients included the application's functionality, temperament survey, and clinical information. After considering users' feedback, the screen functionality, the application's information and idiom, and overall functionality of the application were evaluated and approved by the users. Conclusion: By and large, the developed application could help the patients to receive the best and high-priority treatment protocols based on their own temperament.

Vulnerability of Parkinson's Patients to COVID-19 and Its Consequences and Effects on Them: A Systematic Review.

Introduction: Parkinson's disease (PD) is the second most common neurological disorder. Patients with PD were affected by the COVID-19 pandemic in many different ways. This study's principal purpose is to assess PD patients' vulnerability to COVID-19 and its consequences. Method: This systematic review was performed based on Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA) guidelines. A thorough search was conducted in the Medline (through PubMed) and Scopus databases from inception to January 30, 2022. The Joanna Briggs Institute (JBI) critical appraisal checklist was used to evaluate the studies. Results: Most of the studies (38%) had been conducted in Italy. Of the total number of studies, 17 (58%) were cross-sectional, seven (22%) were cohort, four (12%) were quasiexperimental, two (6%) were case-control, and one (3%) was a qualitative study. The PD duration in patients ranged from 3.26 to 13.40 years (IQR1: 5.7 yrs., median: 3.688 yrs., and IQR3: 8.815 yrs.). Meanwhile, the sample size ranged from 12 to 30872 participants (IQR1: 46, median: 96, and IQR3: 211). Despite worsening PD symptoms in the targeted population (persons with COVID-19 and Parkinson's disease), some studies found PD to be a risk factor for more severe COVID-19 disease. There are many adverse effects during the pandemic period in PD patients such as abnormalities of motor, nonmotor functioning, clinical outcomes, activities of daily living, and other outcomes. Conclusion: This study confirmed the negative effect of the COVID-19 pandemic on health-related quality of life and its determinants in patients with PD and their caregivers. Thus, due to the worsening symptoms of PD patients in the current pandemic, these people should be given more care and supervision to minimize their coronavirus exposure.

MRI-based brain tumor detection using convolutional deep learning methods and chosen machine learning techniques.

BACKGROUND: Detecting brain tumors in their early stages is crucial. Brain tumors are classified by biopsy, which can only be performed through definitive brain surgery. Computational intelligence-oriented techniques can help physicians identify and classify brain tumors. Herein, we proposed two deep learning methods and several machine learning approaches for diagnosing three types of tumor, i.e., glioma, meningioma, and pituitary gland tumors, as well as healthy brains without tumors, using magnetic resonance brain images to enable physicians to detect with high accuracy tumors in early stages. MATERIALS AND METHODS: A dataset containing 3264 Magnetic Resonance Imaging (MRI) brain images comprising images of glioma, meningioma, pituitary gland tumors, and healthy brains were used in this study. First, preprocessing and augmentation algorithms were applied to MRI brain images. Next, we developed a new 2D Convolutional Neural Network (CNN) and a convolutional auto-encoder network, both of which were already trained by our assigned hyperparameters. Then 2D CNN includes several convolution layers; all layers in this hierarchical network have a 2*2 kernel function. This network consists of eight convolutional and four pooling layers, and after all convolution layers, batch-normalization layers were applied. The modified auto-encoder network includes a convolutional auto-encoder network and a convolutional network for classification that uses the last output encoder layer of the first part. Furthermore, six machine-learning techniques that were applied to classify brain tumors were also compared in this study. RESULTS: The training accuracy of the proposed 2D CNN and that of the proposed auto-encoder network were found to be 96.47% and 95.63%, respectively. The average recall values for the 2D CNN and auto-encoder networks were 95% and 94%, respectively. The areas under the ROC curve for both networks were 0.99 or 1. Among applied machine learning methods, Multilayer Perceptron (MLP) (28%) and K-Nearest Neighbors (KNN) (86%) achieved the lowest and highest accuracy rates, respectively. Statistical tests showed a significant difference between the means of the two methods developed in this study and several machine learning methods (p-value < 0.05). CONCLUSION: The present study shows that the proposed 2D CNN has optimal accuracy in classifying brain tumors. Comparing the performance of various CNNs and machine learning methods in diagnosing three types of brain tumors revealed that the 2D CNN achieved exemplary performance and optimal execution time without latency. This proposed network is less complex than the auto-encoder network and can be employed by radiologists and physicians in clinical systems for brain tumor detection.

Features and effects of computer-based games on cognitive impairments in children with autism spectrum disorder: an evidence-based systematic literature review.

INTRODUCTION: Children with Autism Spectrum Disorder (ASD) have different cognitive and intelligence profiles than typical developing individuals. Some of these children need cognitive rehabilitation. This study's main purpose is to provide a systematic review about applying computerized cognitive games for autistic children and to determine the effectiveness of such interventions. MATERIAL AND METHODS: A thorough search of the ISI Web of Science, Medline (through PubMed), Scopus, IEEE Xplore, and APA PsycInfo databases was performed for articles published from inception to May 17, 2022. RESULTS: Of 1746 papers, 28 studies were found to be eligible in this systematic review. Fifteen studies (53.57%) compared a Control Group (CG) with Experimental Groups (EGs), while 13 papers (46.42%) evaluated only the impact of the applied intervention in an experimental group. Major domains of cognitive functions are divided into five main categories: 1. Executive functions, 2. Social cognition/emotions, 3. Attention/concentration, 4. Learning and memory, and 5. Language. In 42.85% (12 studies) of the screened papers, social cognition and emotions were assessed after cognitive rehabilitation. The highest rate of effects reported by studies were related to social cognition enhancement. Of the total number of included studies, 17 studies reported a positive effect at all scales, of which nine were quasi-experimental, and seven were fully experimental. CONCLUSION: Using suitable computerized game-based solutions could enhance cognition indexes in autistic children. Hence, further investigation is needed to determine the real effectiveness of these novel technologies.

An evaluation of the quality of COVID-19 websites in terms of HON principles and using DISCERN tool.

BACKGROUND: As many people relied on information from the Internet for official scientific or academically affiliated information during the COVID-19 pandemic, the quality of information on those websites should be good. OBJECTIVE: The main purpose of this study was to evaluate a selection of COVID-19-related websites for the quality of health information provided. METHOD: Using Google and Yahoo, 36 English language websites were selected, in accordance with the inclusion criteria. The two tools were selected for evaluation were the Health on the Net (HON) Code and the 16-item DISCERN tool. RESULTS: Most websites (39%) were related to information for the public, and a small number of them (3%) concerned screening websites in which people could be informed of their possible condition by entering their symptoms. The result of the evaluation by the HON tool showed that most websites were reliable (53%), and 44% of them were very reliable. Based on the assessment results of the Likert-based 16-item DISCERN tool, the maximum and minimum values for the average scores of each website were calculated as 2.44 and 4.25, respectively. CONCLUSION: Evaluation using two widely accepted tools shows that most websites related to COVID-19 are reliable and useful for physicians, researchers and the public.

The application of wearable smart sensors for monitoring the vital signs of patients in epidemics: a systematic literature review.

Wearable smart sensors are emerging technology for daily monitoring of vital signs with the reducing discomfort and interference with normal human activities. The main objective of this study was to review the applied wearable smart sensors for disease control and vital signs monitoring in epidemics outbreaks. A comprehensive search was conducted in Web of Science, Scopus, IEEE Library, PubMed and Google Scholar databases to identify relevant studies published until June 2, 2020. Main extracted specifications for each paper are publication details, type of sensor, disease, type of monitored vital sign, function and usage. Of 277 articles, 11 studies were eligible for criteria. 36% of papers were published in 2020. Articles were published in 10 different journals and only in the Journal of Medical Systems more than one article was published. Most sensors were used to monitor body temperature, heart rate and blood pressure. Wearable devices (like a helmet, watch, or cuff) and body area network sensors were popular types which can be used monitoring vital signs for epidemic trending. 65% of total papers (n = 6) were conducted by the USA, Malaysia and India. Applying appropriate technological solutions could improve control and management of epidemic disease as well as the application of sensors for continuous monitoring of vital signs. However, further studies are needed to investigate the real effects of these sensors and their effectiveness.

Effects of technology-based educational tools on nursing learning outcomes in intensive care units: a systematic review and meta-analysis.

BACKGROUND: Nurses working in the Intensive Care Unit (ICU), due to the sensitivity and difficulty of tasks, need continuous and scientific training to be able to offer the best performance in difficult situations and use their knowledge in the best way. Also, nursing students spend internships in ICUs and receive special training in practice in the actual center. Educational tools based on new technologies can potentially improve the educational outcomes of nursing in ICUs. OBJECTIVES:  The present study aims to review and evaluate the effect of using technology-based educational tools for training critical care nurses and nursing students. METHODS:  A comprehensive search was conducted to identify peer-reviewed English language articles in Embase, Medline (through PubMed), Scopus, and ISI web of science published from 2010 to Feb 18, 2022. The studies that examined the effectiveness of technology-based educational interventions with control groups were included. The risk of bias in each study was assessed using the Cochrane Collaboration's tool. Also, we used Standard Mean Difference (SMD) to estimate the effect of technology-based educational tools on learning outcomes. All meta-analyses were performed with a random effects model in Stata Ver.16. RESULTS:  Altogether, ten studies were eligible for the quality assessment and systematic review, while one study that had not reported the pre-intervention analysis was excluded from the meta-analysis. Nine studies were considered to have a low RoB regarding reporting ways, and one of them showed a high risk. Performance and selection bias caused a high risk in six and five of the studies, respectively. In the meta-analysis, improvement in knowledge (SMD = 0.91), skills (SMD = 0.52), and self-confidence (SMD = 0.96) was noticed by applying technology-based educational tools. CONCLUSION: It can be offered that if the learning method based on the new technologies tested is more effective than conventional teaching methods, they are likely to improve the learning outcome significantly. The new-developed tools also have great potential in improving health care functions among nurses or nursing students as well as enhancing the quality of life and patient satisfaction.

A smartphone-based self-care application for patients with urinary tract stones: identification of information content and functional capabilities.

PURPOSE: This study aimed to identify and validate the information content and functional capabilities of a smartphone-based application for the self-care of patients with urinary tract stones. METHODS AND MATERIALS: First, by reviewing studies and urology-oriented books, studying 214 medical records, and consulting with specialists, the information items and basic capabilities of the application were identified, and in the next stage, a researcher-made questionnaire was designed based on the information obtained from the previous step. Then, experts' opinions were considered to confirm the validity and reliability of the questionnaire; the designed questionnaire was distributed among various participants. Finally, the application's leading information elements, contents, and functional capabilities were explored by analyzing the questionnaire results. RESULTS: To conduct the survey, 101 patients with Urinary Stone Diseases (USD), 32 urologists and nephrologists, 11 nurses, and six other specialists were recruited. After analyzing the results of the filled questionnaire, 21 information elements and nine surveyed capabilities that were more important than others were selected to be used in designing the application. Some of the principal information elements that were used in the application design include: the cause of various stones in the body, clinical manifestations, laboratory results, treatments of various stones, the role of environmental factors in the treatment, the role of nutrition in the treatment and formation of stones, and different diagnostic methods. Some of the important features of the application include: medication and fluid intake reminders, laboratory test reminders, radiography and periodic examination reminders, surgical history, and easy access to medical centers for information. The mean score of information elements was 75.07 from the patients' perspective, 65.09 from the physicians' perspective, and 80.09 from the nurses' perspective. Also, the mean score of application capabilities was 31.89 from the patients' perspective, 30.37 from the physicians' perspective, and 35.09 from the nurses' perspective. The difference in the mean scores of the above variables was statistically significant (p < 0.05) in both layers. CONCLUSION: In this study, informational and functional needs and capabilities were presented for designing a mobile-based application that helps in disease management in patients with urinary tract stones.

Computerized Simulation Education on Physiotherapy Students' Skills and Knowledge: A Systematic Review.

Introduction: Applying computerized simulation education tool for learning in medical domains is widely used in many countries. This review is aimed at systematically investigating the computerized simulation tools developed to educate physiotherapy students and determine the effectiveness of these interventions. Methods: A comprehensive search was conducted in Medline (through PubMed) and Scopus databases from inception to Sept. 10, 2022. The studies that examined the effectiveness of computerized simulation-based interventions were included. Results: Sixteen studies were included in this systematic review. All included examinations were ranked "good" or "low risk of bias" based on the criteria utilized in the Joanna Briggs Institute (JBI) scale and the Effective Public Health Practice Project (EPHPP) tool. Most of the articles (43%) were conducted in the USA and 25% in Australia. In 43% of the total studies, the study population was only physiotherapy students, and in 12.5% of them, the scope of education was related to practical skills training. Three of the 16 reviewed articles presented positive qualitative results; thirteen quantitative investigations also declared statistically positive effects. Positive effects have been seen in areas such as improving professional and behavioral abilities, improving knowledge and self-confidence, and reducing stress. The sample size of the studies ranged from eight to 162 participants. The limited sample sizes in groups, lack of interaction, and short follow-up duration were the most consistent limitations evident within the included studies. Conclusion: Computerized simulation education approaches can help to improve physiotherapy students' skills and knowledge. They also have great potential to reduce learning costs and increase the quality of education.

Medical Informaticians' Skills and Competencies to Achieve Roles and Opportunities: A Qualitative Study.

For Medical Informatics graduates, there is no compatibility between the training knowledge and skills at universities and the job requirements. This study aimed to determine the skills and competencies requirements for medical informatics graduates and possible job positions in an emerging discipline. This qualitative study was conducted using a questionnaire developed by the researchers. Nine independent medical informatics professionals assessed the initial draft of this tool to determine its face and content validity, and reliability. The questionnaire was distributed among 80 medical informaticians with a doctorate or a master's degree. In this study, items with an average of 4 and higher were confirmed; out of the 78 items, 66 were approved. The highest number of unapproved items was related to managerial knowledge and skills. Research knowledge, training skills, individual skills, technical capacities, specific skills in the health industry, and managerial skills are the main areas that graduates must learn. This survey can help develop a curriculum and job descriptions for medical informatics.

Artificial Intelligence Approaches on X-ray-oriented Images Process for Early Detection of COVID-19.

Background: COVID-19 is a global public health problem that is crucially important to be diagnosed in the early stages. This study aimed to investigate the use of artificial intelligence (AI) to process X-ray-oriented images to diagnose COVID-19 disease. Methods: A systematic search was conducted in Medline (through PubMed), Scopus, ISI Web of Science, Cochrane Library, and IEEE Xplore Digital Library to identify relevant studies published until 21 September 2020. Results: We identified 208 papers after duplicate removal and filtered them into 60 citations based on inclusion and exclusion criteria. Direct results sufficiently indicated a noticeable increase in the number of published papers in July-2020. The most widely used datasets were, respectively, GitHub repository, hospital-oriented datasets, and Kaggle repository. The Keras library, Tensorflow, and Python had been also widely employed in articles. X-ray images were applied more in the selected articles. The most considerable value of accuracy, sensitivity, specificity, and Area under the ROC Curve was reported for ResNet18 in reviewed techniques; all the mentioned indicators for this mentioned network were equal to one (100%). Conclusion: This review revealed that the application of AI can accelerate the process of diagnosing COVID-19, and these methods are effective for the identification of COVID-19 cases exploiting Chest X-ray images.

Evaluating the usability of a national health information system with heuristic method.

BACKGROUND: Hospital Statistics and Information System is one of the most important health information systems in Iran used in all hospitals in this country. Usability problems can reduce the speed and precision of users when interacting with this system. This study aimed to identify the usability problems of a national health system called "AVAB". MATERIALS AND METHODS: This descriptive cross-sectional study was conducted in 2020, and three experts evaluated the usability of this system independently by the heuristic evaluation method. Nielsen's usability principles were used to identify usability problems and to classify their severity. RESULTS: A total of 86 unique problems were identified. The highest number of problems were related to the two principles of "help and documentation" and "match between system and the real world" with 23 and 11 usability problems, respectively. The lowest number of problems were related to the two principles of "visibility of system status" and "help users recognize, diagnose, and recover from errors," each with three problems. 58.1% of the identified problems were in the group of major and catastrophic problems. CONCLUSIONS: With the help of heuristic evaluation method, a significant number of usability problems of Hospital Statistics and Information System were identified. Most of the identified problems were major and catastrophic, and it is necessary to solve these problems by the designers and developers of this system.

Cognitive rehabilitation in people with autism spectrum disorder: a systematic review of emerging virtual reality-based approaches.

INTRODUCTION: Emerging virtual technologies and cognitive rehabilitation methods are two new treatment approaches that can be used to strengthen cognitive functions in Autism Spectrum Disorder (ASD). The main aim of this study was to examine the effect of using virtual reality-based approaches on cognitive disorders of children and adults with ASD. METHODS: This systematic review was conducted on scientific papers to determine the effects of virtual reality-based technologies on the cognitive functions of children and adults with ASD. We identified 688 studies related to this topic and filtered them down to 17 articles, and then extracted the effects of interventions on cognitive outcomes. RESULTS: A total of 17 studies met the inclusion criteria, in which 226 persons with ASD had taken place. The sample size in the selected studies ranged from 1 to 56 participants (Median: 8, Q1: 3.5, Q3: 15.5). Four of the studies were case-control studies, ten were pre-test/post-test studies, and three were Randomized Control Trials (RCTs). Results of 16 studies showed significant progress in various cognitive indexes, such as task learning, attention, executive functioning, and daily skills in people with ASD. In most studies, virtual technologies had beneficial effects on reducing cognitive problems, but existing limitations could reduce their effectiveness. These limitations included the cost of virtual reality devices, inappropriate size of software, the weight of devices, potential addiction, intolerance of wearing glasses or headsets by people with autism (especially in children), and the possibility of eye injury. CONCLUSION: Applying appropriate virtual-based approaches could improve cognitive indexes in people with ASD. However, further studies are needed to investigate the real effects of these technologies in the long run.

Predicting the survival of kidney transplantation: design and evaluation of a smartphone-based application.

BACKGROUND: Prediction of graft survival for Kidney Transplantation (KT) is considered a risky task due to the scarcity of donating organs and the use of health care resources. The present study aimed to design and evaluate a smartphone-based application to predict the survival of KT in patients with End-Stage Renal Disease (ESRD). METHOD: Based on the initial review, a researcher-made questionnaire was developed to assess the information needs of the application through urologists and nephrologists. By using information obtained from the questionnaire, a checklist was prepared, and the information of 513 patients with kidney failure was collected from their records at Sina Urological Research Center. Then, three data mining algorithms were applied to them. The smartphone-based application for the prediction of kidney transplant survival was designed, and a standard usability assessment questionnaire was used to evaluate the designed application. RESULTS: Three information elements related to the required data in different sections of demographic information, sixteen information elements related to patient clinical information, and four critical capabilities were determined for the design of the smartphone-based application. C5.0 algorithm with the highest accuracy (87.21%) was modeled as the application inference engine. The application was developed based on the PhoneGap framework. According to the participants' scores (urologists and nephrologists) regarding the usability evaluation of the application, it can be concluded that both groups participating in the study could use the program, and they rated the application at a "good" level. CONCLUSION: Since the overall performance or usability of the smartphone-based app was evaluated at a reasonable level, it can be used with certainty to predict kidney transplant survival.

Educational approaches for patients with heart surgery: a systematic review of main features and effects.

INTRODUCTION: Patients who undergo heart surgery are exposed to mental and physical difficulties after discharge from hospital. They often need support and follow-up after discharge. The use of educational approaches or solutions before or after heart surgery can increase patients' knowledge on the post-operative complications and self-care. The main purpose of this systematic review is to determine the applications of educational approaches and investigate the effects of these approaches on patients with heart surgery. METHOD AND MATERIEL: A thorough search was conducted in Medline (through PubMed), Scopus, ISI web of science to select related articles published between 2011 and May 2022. All of the retrieved papers were screened according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. RESULTS: A total of 29 articles were obtained from the search, which included in this systematic review after being assessed based on inclusion and exclusion criteria. Most of the articles (n = 10, 34.48%) had been conducted in Canada and Iran, with the most significant number published in 2016. Out of 29 studies, 23 were experimental studies, and six were observational-analytical studies. The number of participants in the studies ranged from 11 to 600 (IQR1: 57.5, median: 88, IQR3: 190). In 28 (96.55%) studies, the educational approaches had a significant effect on clinical, economic or patient-reported outcomes. The greatest effect reported by the studies was related to clinical outcomes such as patient care improvement or change in clinical practice. The most effects in the patient-reported outcomes were related to improving patient satisfaction and patient knowledge. In terms of global rating scores, 17.24% of the included studies were considered as weak, 20.68% as moderate, and 62.06% as strong. CONCLUSION: The results of systematic review showed that the use of educational approaches by patients before and after heart surgery can have significant effects on reducing stress and financial burden, and increasing the quality of care and level of knowledge in patients.

Identifying a minimum data set as a necessity to design a web-based personal health record for patients under chronic dialysis.

Objective: Many people suffer from kidney disease, and self-management is essential in these patients. Personal health record (PHR) can be used as a tool to improve self-management in these patients. This study aimed to identify a minimum data set (MDS) of PHR in dialysis patients. Methods: This descriptive and cross-sectional study was conducted in 2019, and national and international scientific literature entitled "Personal Health Record," "Electronic Personal Health Record," "Dialysis Patient Portal," "Dialysis Health Record," and "Dialysis Information Needs" by content analysis method was reviewed. A questionnaire with 14 items was designed to examine patients' problems and data needs based on the review of scientific literature and web-based PHRs. Based on the patients' survey and the review of scientific literature, a questionnaire with 114 questions was designed. Finally, with experts' opinions, data elements were determined. Results: An MDS for developing web-based PHR for patients under chronic dialysis was created with 17 data classes including demographic information, insurance information, contact information in case of emergency, information on dialysis sessions, physicians information, dialysis center information, information on individual measured values (blood pressure, blood sugar, and weight), disease history information, information on surgical procedures and operations, history of visits, allergies, vaccinations, family history, drugs, laboratory tests, diet, and education materials for the patient. Conclusion: In this study, an MDS was developed for a web-based PHR for dialysis patients. The use of standard data can help collect the data that is essential to improve the patient's health and track his medical condition.