The efficacy of virtual reality for upper limb rehabilitation in stroke patients: a systematic review and meta-analysis.

BACKGROUND: Stroke frequently gives rise to incapacitating motor impairments in the upper limb. Virtual reality (VR) rehabilitation has exhibited potential for augmenting upper extremity recovery; nonetheless, the optimal techniques for such interventions remain a topic of uncertainty. The present systematic review and meta-analysis were undertaken to comprehensively compare VR-based rehabilitation with conventional occupational therapy across a spectrum of immersion levels and outcome domains. METHODS: A systematic search was conducted in PubMed, IEEE, Scopus, Web of Science, and PsycNET databases to identify randomized controlled trials about upper limb rehabilitation in stroke patients utilizing VR interventions. The search encompassed studies published in the English language up to March 2023. The identified studies were stratified into different categories based on the degree of immersion employed: non-immersive, semi-immersive, and fully-immersive settings. Subsequent meta-analyses were executed to assess the impact of VR interventions on various outcome measures. RESULTS: Of the 11,834 studies screened, 55 studies with 2142 patients met the predefined inclusion criteria. VR conferred benefits over conventional therapy for upper limb motor function, functional independence, Quality of life, Spasticity, and dexterity. Fully immersive VR showed the greatest gains in gross motor function, while non-immersive approaches enhanced fine dexterity. Interventions exceeding six weeks elicited superior results, and initiating VR within six months post-stroke optimized outcomes. CONCLUSIONS: This systematic review and meta-analysis demonstrates that adjunctive VR-based rehabilitation enhances upper limb motor recovery across multiple functional domains compared to conventional occupational therapy alone after stroke. Optimal paradigms likely integrate VR's immersive capacity with conventional techniques. TRIAL REGISTRATION: This systematic review and meta-analysis retrospectively registered in the OSF registry under the identifier [ https://doi.org/10.17605/OSF.IO/YK2RJ ].

Exploring the geospatial epidemiology of breast cancer in Iran: identifying significant risk factors and spatial patterns for evidence-based prevention strategies.

BACKGROUND: Breast Cancer (BC) is a formidable global health challenge, and Iran is no exception, with BC accounting for a significant proportion of women's malignancies. To gain deeper insights into the epidemiological characteristics of BC in Iran, this study employs advanced geospatial techniques and feature selection methods to identify significant risk factors and spatial patterns associated with BC incidence. METHODS: Using rigorous statistical methods, geospatial data from Iran, including cancer-related, sociodemographic, healthcare infrastructure, environmental, and air quality data at the provincial level, were meticulously analyzed. Age-standardized incidence rates (ASR) are calculated, and different regression models are used to identify significant variables associated with BC incidence. Spatial analysis techniques, including global and local Moran's index, geographically weighted regression, and Emerging hotspot analysis, were utilized to examine geospatial patterns, identify clustering and hotspots, and assess spatiotemporal distribution of BC incidence. RESULTS: The findings reveal that BC predominantly affects women (98.03%), with higher incidence rates among those aged 50 to 79. Isfahan (ASR = 26.1) and Yazd (ASR = 25.7) exhibit the highest rates. Significant predictors of BC incidence, such as marriage, tertiary education attainment rate, physician-to-population ratio, and PM2.5 air pollution, are identified through regression models. CONCLUSION: The study's results provide valuable information for the development of evidence-based prevention strategies to reduce the burden of BC in Iran. The findings underscore the importance of early detection, health education campaigns, and targeted interventions in high-risk clusters and adjacent regions. The geospatial insights generated by this study have implications for policy-makers, researchers, and public health practitioners, facilitating the formulation of effective BC prevention strategies tailored to the unique epidemiological patterns in Iran.

Stability monitoring of patients with myasthenia gravis using a mobile-based application.

Background: Failure in early diagnosis of myasthenia gravis (MG) and the risks of taking certain medications and undergoing surgery and anesthesia can lead to severe respiratory disorders and death. However, there are therapeutic measures that significantly control the disease and improve individual's functionality. Methods: First, an expert panel was formed, and a needs assessment questionnaire was prepared for the information elements and the capabilities required for the application and provided to neurologists with a subspecialty fellowship in neuromuscular diseases. Then, based on the analyzed results, the application was designed and created in 2 versions (physician and patient), and in 2 languages (Persian and English). Eventually, a questionnaire for user interaction and satisfaction was provided to 5 relevant physicians to evaluate the application. Results: The results showed that neurologists considered all items of the needs assessment questionnaire to be 100% essential. The capabilities of the application included registering the medication name and dose, recording symptoms and complaints by the patient, completing standard questionnaires, online chat, medication reminder, sending alerts to the doctor when the patient is unwell, and providing a variety of reports. The usability evaluation showed that neurologists evaluated the application at a good level with the average score of 8.23 ± 0.47 (out of 9 points). Conclusion: In the long run, using this technology can reduce costs, improve patients' quality of life (QOL) and health care, change health behaviors, and ultimately, improve individual's health.

Designing and evaluating the children's developmental motor disorders system: an experience from a developing country.

BACKGROUND: Developmental disorders are a prevalent problem in the health sector of low- and middle-income countries (LMICs), and children in these countries are at greater risk. A registry system is helpful and vital to monitoring and managing this disease. OBJECTIVE: The present study aims to develop an electronic registry system for children's developmental motor disorders. METHODS: The study was conducted between 2019 and 2020 in three phases. First, the requirements of the system were identified. Second, UML diagrams were first drawn using Microsoft Visio software. Then, the system was designed using the ASP.NET framework in Visual Studio 2018, and the C# programming language was used in the NET 4.5 technology platform. In the third phase, system usability was evaluated from the users' viewpoint. RESULTS: The findings of this research included system requirements, a conceptual model, and a web-based system. The client and system server connection was established through the IP/TCP communication protocol in a university physical network. End users approved the system with an agreement rate of 87.14%. CONCLUSION: The study's results can be used as a model for designing and developing systems related to children's developmental movement disorders in other countries. It is also suggested as a valuable platform for research and improving the management of this disease.

Virtual Reality and Cardiac Diseases: A Systematic Review of Applications and Effects.

Introduction: Cardiac diseases have grown significantly in recent years, causing many deaths globally. Cardiac diseases can impose a significant economic burden on societies. The development of virtual reality technology has attracted the attention of many researchers in recent years. This study aimed to investigate the applications and effects of virtual reality (VR) technology on cardiac diseases. Methods: A comprehensive search was carried out in four databases, including Scopus, Medline (through PubMed), Web of Science, and IEEE Xplore to identify related articles published until May 25, 2022. Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA) guideline for systematic reviews was followed. All randomized trials that investigated the effects of virtual reality on cardiac diseases were included in this systematic review. Results: Twenty-six studies were included in this systematic review. The results illustrated that virtual reality applications in cardiac diseases can be classified in three categories of physical rehabilitation, psychological rehabilitation, and education/training. This study revealed that the use of virtual reality in psychological and physical rehabilitation can reduce stress, emotional tension, Hospital Anxiety and Depression Scale (HADS) total score, anxiety, depression, pain, systolic blood pressure, and length of hospitalization. Finally, the use of virtual reality in education/training can enhance technical performance, increase the speed of procedures, and improve the user's skills, level of knowledge, and self-confidence as well as facilitate learning. Also, the most limitations mentioned in the studies included small sample size and lack of or short duration of follow-up. Conclusions: The results showed that the positive effects of using virtual reality in cardiac diseases are much more than its negative effects. Considering that the most limitations mentioned in the studies were the small sample size and short duration of follow-up, it is necessary to conduct studies with adequate methodological quality to report their effects in the short term and long term.

Developing a mobile health application for wound telemonitoring: a pilot study on abdominal surgeries post-discharge care.

BACKGROUND: Many early signs of Surgical Site Infection (SSI) developed during the first thirty days after discharge remain inadequately recognized by patients. Hence, it is important to use interactive technologies for patient support in these times. It helps to diminish unnecessary exposure and in-person outpatient visits. Therefore, this study aims to develop a follow-up system for remote monitoring of SSIs in abdominal surgeries. MATERIAL AND METHODS: This pilot study was carried out in two phases including development and pilot test of the system. First, the main requirements of the system were extracted through a literature review and exploration of the specific needs of abdominal surgery patients in the post-discharge period. Next extracted data was validated according to the agreement level of 30 clinical experts by the Delphi method. After confirming the conceptual model and the primary prototype, the system was designed. In the pilot test phase, the usability of the system was qualitatively and quantitatively evaluated by the participation of patients and clinicians. RESULTS: The general architecture of the system consists of a mobile application as a patient portal and a web-based platform for patient remote monitoring and 30-day follow-up by the healthcare provider. Application has a wide range of functionalities including collecting surgery-related documents, and regular assessment of self-reported symptoms via systematic tele-visits based on predetermined indexes and wound images. The risk-based models embedded in the database included a minimum set with 13 rules derived from the incidence, frequency, and severity of SSI-related symptoms. Accordingly, alerts were generated and displayed via notifications and flagged items on clinicians' dashboards. In the pilot test phase, out of five scheduled tele-visits, 11 (of 13) patients (85%), completed at least two visits. The nurse-centered support was very helpful in the recovery stage. Finally, the result of a pilot usability evaluation showed users' satisfaction and willingness to use the system. CONCLUSION: Implementing a telemonitoring system is potentially feasible and acceptable. Applying this system as part of routine postoperative care management can provide positive effects and outcomes, especially in the era of coronavirus disease when more willingness to telecare service is considered.

Ranking the Critical Success Factors for Hospital Information Systems Using a Fuzzy Analytical Hierarchy Process.

The design, development, and maintenance of hospital information systems face major challenges, which ultimately cause failures of these information systems. This study aimed to identify and rank critical success factors for hospital information systems by applying a fuzzy analytical hierarchy process. Potential critical success factors that could contribute to the success of hospital information systems were identified and extracted through a systematic review of the relevant studies. A questionnaire containing the critical success factors was designed and distributed to 250 hospital information system professionals. The hierarchical structure of the critical success factors was defined by using an exploratory factor analysis, and pairwise comparison matrices of the fuzzy analytical hierarchy process model were designed based on the identified factor structure. As a result, 50 potential critical success factors were extracted from 21 articles, and their content validity and face validity were assessed by the experts. Based on the exploratory factor analysis results, 36 critical success factors were classified into seven dimensions: organizational fitness, user-friendliness, maintainability, portability, productivity, reliability, and organizational and external support. The fuzzy analytical hierarchy process results indicated that reliability, user-friendliness, and organizational fitness (with 20.3, 19.9, and 18 points, respectively) had the greatest impact on the success of hospital information systems. The findings revealed that managers and policymakers should consider these critical success factors in designing and developing hospital information systems.

The willingness and attitudes of speech-language pathologists towards the use of mobile health technology: a survey study.

BACKGROUND: Mobile health (mHealth) technology could be used in different ways to treat various speech and language disorders. The attitude of speech-language pathologists (SLPs) towards this technology and their willingness to use it can play a significant role in the success of the therapies they provide. This study was conducted to investigate the willingness and attitude of SLPs towards the use of mHealth technology. METHODS: This cross-sectional study was conducted from September 2021 to April 2022 in Iran. A researcher-made questionnaire consisting of three parts (information related to demographic variables, attitude and willingness) was designed based on the past studies, and then given to all SLPs throughout Iran. Data were analyzed by SPSS software, using descriptive and inferential statistics (frequency, mean, Fisher's exact test, and analysis of variance). Also, the SLPs' willingness to use the desired technology was interpreted as a percentage as follows: 0-20% = not at all willing, 21-40% = slightly willing, 41-60% = moderately willing, 61-80% = highly willing, and above 80% = extremely willing. RESULTS: One hundred sixty speech-language pathologists from all over Iran participated in this study. The results showed that the willingness of 65.25% of SLPs to use the mentioned technology was at a good level, and according to the mentioned category, they had a high willingness to use this technology. In regard to the attitude of SLPs, the findings showed that SLPs believed that patients receive a higher quality of care during in-person visits than through mHealth technology. Also, this survey showed that SLPs were more inclined to use this technology to answer patients' questions. Non-payment of services provided through mHealth technology and privacy concerns were the reasons for the lack of use of this technology by SLPs. CONCLUSIONS: SLPs are willing to use mHealth technology after solving the related challenges, including payment of costs and privacy concerns. However, SLPs believed that this technology will not be a suitable alternative to face-to-face sessions.

Opportunities and challenges of virtual reality-based interventions for patients with breast cancer: a systematic review.

BACKGROUND: Breast cancer is one of the most common cancers diagnosed worldwide and the second leading cause of death among women. Virtual reality (VR) has many opportunities and challenges for breast cancer patients' rehabilitation and symptom management. The purpose of this systematic review is to look into the benefits and drawbacks of VR interventions for breast cancer patients. METHODS: A systematic search was conducted on PubMed, Web of Science, Scopus, IEEE, and the Cochrane Library, from inception until February 6, 2022. The inclusion criteria were: (1) original studies without restriction in study design; (2) a study population consisting of patients with breast cancer; (3) any type of VR-based interventions (immersive and non-immersive); and (5) studies published in English. To assess the risk of bias, the Effective Public Health Practice Project (EPHPP) Tool was used. RESULTS: Eighteen articles were included in this systematic review. The result showed that VR could provide many opportunities for patients with breast cancer, including reducing anxiety, time perception, pain, fatigue, chemotherapy-related symptom distress levels, and depression severity, as well as improvement in the range of motion, strength, and function. Cybersickness symptoms, the weight of headsets and helmets, the quality of the visual image, and the cost of the equipment are some of the challenges in using this technology on these patients. CONCLUSIONS: The systematic review showed that VR interventions have opportunities and challenges for patients with breast cancer. VR can be effective for rehabilitation and symptom management and is used in different stages of treatment to improve the condition of patients with breast cancer. However, before using it, the researcher should consider its challenges.

The Persian Version of the Mobile Application Rating Scale (MARS-Fa): Translation and Validation Study.

BACKGROUND: Approximately 110 million Farsi speakers worldwide have access to a growing mobile app market. Despite restrictions and international sanctions, Iran's internal mobile health app market is growing, especially for Android-based apps. However, there is a need for guidelines for developing health apps that meet international quality standards. There are also no tools in Farsi that assess health app quality. Developers and researchers who operate in Farsi could benefit from such quality assessment tools to improve their outputs. OBJECTIVE: This study aims to translate and culturally adapt the Mobile Application Rating Scale in Farsi (MARS-Fa). This study also evaluates the validity and reliability of the newly developed MARS-Fa tool. METHODS: We used a well-established method to translate and back translate the MARS-Fa tool with a group of Iranian and international experts in Health Information Technology and Psychology. The final translated version of the tool was tested on a sample of 92 apps addressing smartphone addiction. Two trained reviewers completed an independent assessment of each app in Farsi and English. We reported reliability and construct validity estimates for the objective scales (engagement, functionality, aesthetics, and information quality). Reliability was based on the evaluation of intraclass correlation coefficients, Cronbach α and Spearman-Brown split-half reliability indicators (for internal consistency), as well as Pearson correlations for test-retest reliability. Construct validity included convergent and discriminant validity (through item-total correlations within the objective scales) and concurrent validity using Pearson correlations between the objective and subjective scores. RESULTS: After completing the translation and cultural adaptation, the MARS-Fa tool was used to assess the selected apps for smartphone addiction. The MARS-Fa total scale showed good interrater reliability (intraclass correlation coefficient=0.83, 95% CI 0.74-0.89) and good internal consistency (Cronbach α=.84); Spearman-Brown split-half reliability for both raters was 0.79 to 0.93. The instrument showed excellent test-retest reliability (r=0.94). The correlations among the MARS-Fa subdomains and the total score were all significant and above r=0.40, suggesting good convergent and discriminant validity. The MARS-Fa was positively and significantly correlated with subjective quality (r=0.90, P<.001), and so were the objective subdomains of engagement (r=0.85, P<.001), information quality (r=0.80, P<.001), aesthetics (r=0.79, P<.001), and functionality (r=0.57, P<.001), indicating concurrent validity. CONCLUSIONS: The MARS-Fa is a reliable and valid instrument to assess mobile health apps. This instrument could be adopted by Farsi-speaking researchers and developers who want to evaluate the quality of mobile apps. While we tested the tool with a sample of apps addressing smartphone addiction, the MARS-Fa could assess other domains or issues since the Mobile App Rating Scale has been used to rate apps in different contexts and languages.

Developing a Clinical Decision Support System for Prediction Postoperative Coronary Artery Bypass Grafting Infection in Diabetic Patients.

Background: Postoperative infection in Coronary Artery Bypass Graft (CABG) is one of the most common complications for diabetic patients, due to an increase in the hospitalization and cost. To address these issues, it is necessary to apply some solutions. Objective: The study aimed to the development of a Clinical Decision Support System (CDSS) for predicting the CABG postoperative infection in diabetic patients. Material and Methods: This developmental study is conducted on a private hospital in Tehran in 2016. From 1061 CABG surgery medical records, we selected 210 cases randomly. After data gathering, we used statistical tests for selecting related features. Then an Artificial Neural Network (ANN), which was a one-layer perceptron network model and a supervised training algorithm with gradient descent, was constructed using MATLAB software. The software was then developed and tested using the receiver operating characteristic (ROC) diagram and the confusion matrix. Results: Based on the correlation analysis, from 28 variables in the data, 20 variables had a significant relationship with infection after CABG (P<0.05). The results of the confusion matrix showed that the sensitivity of the system was 69%, and the specificity and the accuracy were 97% and 84%, respectively. The Receiver Operating Characteristic (ROC) diagram shows the appropriate performance of the CDSS. Conclusion: The use of CDSS can play an important role in predicting infection after CABG in patients with diabetes. The designed software can be used as a supporting tool for physicians to predict infections caused by CABG in diabetic patients as a susceptible group. However, other factors affecting infection must also be considered for accurate prediction.

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.

Application of Digital Games for Speech Therapy in Children: A Systematic Review of Features and Challenges.

Introduction: Treatment of speech disorders during childhood is essential. Many technologies can help speech and language pathologists (SLPs) to practice speech skills, one of which is digital games. This study aimed to systematically investigate the games developed to treat speech disorders and their challenges in children. Methods: A comprehensive search was conducted in four databases, including Medline (through PubMed), Scopus, Web of Science, and IEEE Xplore, to retrieve English articles published by July 14, 2021. The articles in which a digital game was developed to treat speech disorders in children were included in the study. Then, the features of the designed games and their challenges were extracted from the studies. Results: After reviewing the full texts of 69 articles and assessing them in terms of inclusion and exclusion criteria, 27 articles were included in the systematic review. In these articles, 59.25% of the games had been developed in English language and children with hearing impairments had received much attention from researchers compared to other patients. Also, the Mel-Frequency Cepstral Coefficients (MFCC) algorithm and the PocketSphinx speech recognition engine had been used more than any other speech recognition algorithm and tool. In terms of the games, 48.15% had been designed in a way that children could practice with the help of their parents. The evaluation of games showed a positive effect on children's satisfaction, motivation, and attention during speech therapy exercises. The biggest barriers and challenges mentioned in the studies included sense of frustration, low self-esteem after several failures in playing games, environmental noise, contradiction between games levels and the target group's needs, and problems related to speech recognition. Conclusion: The results of this study showed that the games positively affect children's motivation to continue speech therapy, and they can also be used as the SLPs' aids. Before designing these tools, the obstacles and challenges should be considered, and also, the solutions should be suggested.

Validity, Reliability, and Optimal Cut-off Scores of the WHO-5, PHQ-9, and PHQ-2 to Screen Depression Among University Students in Iran.

This study aimed to investigate the validity, reliability, and optimal cut-off points for the Patient Health Questionnaire-2 (PHQ-2), Patient Health Questionnaire-9 (PHQ-9), and Well-being Index (WHO-5) to screen mild depression among 400 Iranian students who completed these tools and Beck Depression Inventory (BDI-13). Further, a psychiatrist diagnosed the depression by using the "Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders." The validity and internal consistency of tools assessed and the accuracy were computed using the receiver operating characteristic (ROC) and area under the curve (AUC). The internal consistency values of PHQ-2, PHQ-9, and WHO-5 were .73, .88, and .94, respectively. The PHQ-2 (.53), PHQ-9 (.60), and WHO-5 (.54) were significantly associated with the BDI. The PHQ-2, PHQ-9, and WHO-5 had optimal cut-off points of 2, 5, and 9 with an AUC of .809, .851, and .823, respectively. Based on these findings, it is recommended to use the PHQ-9 for mild depression screening among medical university students in Iran because of its high sensitivity and specificity.

Applying Game-Based Approaches for Physical Rehabilitation of Poststroke Patients: A Systematic Review.

OBJECTIVE: A large number of patients need critical physical rehabilitation after the stroke. This study aimed to review and report the result of published studies, in which newly emerged games were employed for physical rehabilitating in poststroke patients. MATERIALS AND METHODS: This systematic review study was performed based on the PRISMA method. A comprehensive search of PubMed, Scopus, IEEE Xplore Digital Library, and ISI Web of Science was conducted from January 1, 2014, to November 9, 2020, to identify related articles. Studies have been entered in this review based on inclusion and exclusion criteria, in which new games have been used for physical rehabilitation. RESULTS: Of the 1326 retrieved studies, 60 of them met our inclusion criteria. Virtual reality-oriented games were the most popular type of physical rehabilitation approach for poststroke patients. "The Nintendo Wii Fit" game was used more than other games. The reviewed games were mostly operated to balance training and limb mobilization. Based on the evaluation results of the utilized games, only in three studies, applied games were not effective. In other studies, games had effective outcomes for target body members. CONCLUSIONS: The results indicate that modern games are efficient in poststroke patients' physical rehabilitation and can be used alongside conventional methods.

Mobile-Based and Cloud-Based System for Self-management of People With Type 2 Diabetes: Development and Usability Evaluation.

BACKGROUND: As the use of smartphones and mobile apps is increasing, mobile health (mHealth) can be used as a cost-effective option to provide behavioral interventions aimed at educating and promoting self-management for chronic diseases such as diabetes. Although many mobile software apps have been developed for this purpose, they usually lack a theoretical foundation and do not follow the guidelines suggested for evidence-based practice. Therefore, this study aimed to develop a theory-based self-management app for people with type 2 diabetes and provide an app based on a needs assessment analysis. OBJECTIVE: This paper describes the development and usability evaluation of a cloud-based and mobile-based diabetes self-management app designed to help people with diabetes change their health behavior and also enable remote monitoring by health care providers. METHODS: The development of this mHealth solution comprises 3 phases. Phase I: feature extraction of the Android apps that had a user rating of 4 stars or more and review of papers related to mHealth for diabetes self-management were performed followed by seeking expert opinions about the extracted features to determine the essential features of the app. Phase II: design and implementation included selecting which behavioral change and structural theories were to be applied the app and design of the website. Phase III: evaluation of the usability and user experience of the mobile app by people with diabetes and the portal by health care providers using the User Experience Questionnaire. RESULTS: The developed mobile app includes modules that support several features. A person's data were entered or collected and viewed in the form of graphs and tables. The theoretical foundation of behavioral intervention is the transtheoretical model. Users were able to receive customized messages based on the behavioral change preparation stage using the Kreuter algorithm. The clinician's portal was used by health care providers to monitor the patients. The results of the usability evaluation revealed overall user satisfaction with the app. CONCLUSIONS: Mobile- and cloud-based systems may be an effective tool for facilitating the modification of self-management of chronic care. The results of this study showed that the usability of mobile- and cloud-based systems can be satisfactory and promising. Given that the study used a behavioral model, assessment of the effectiveness of behavior change over time requires further research with long-term follow-up.

A minimum data set of user profile or electronic health record for chemical warfare victims' recommender system.

BACKGROUND: There are many people who are suffering from a variety of physical and mental illnesses due to the chemical attacks. There are various technologies such as recommender systems that can identify the main concerns related to health and make efforts to address them. To design and develop a recommender system, preparation of data source of this system should be considered. The aim of this study was to determine the minimum data set for user profile or user's electronic health record in chemical warfare victims' recommender system. METHODS: This applied descriptive, cross-sectional study which was conducted in 2017. A questionnaire was developed by the authors from the data elements that were collected using the data extraction form from the studied sources. Content validity of the questionnaire was confirmed by using the experts. Test-retest method was used to determine the reliability of the questionnaire. The reliability of the questionnaire with Cronbach's alpha coefficient was confirmed as 84%. The questionnaire were submitted for related experts based on Delphi method by email or in person. Data resulting from the Delphi technique with descriptive statistics methods in SPSS software were analyzed. RESULTS: Forty-seven nonclinical data elements and 181 clinical data elements were classified. CONCLUSION: Determining minimum data set of user profile or electronic health record in the recommender system for chemical warfare victims helps the health authorities to implement the recommender system which demonstrates chemical warfare victims' needs.

Nursing process education: A review of methods and characteristics.

The concepts of the nursing process have been assigned as important plans for the curricula and continuing education programs in the nursing discipline. This paper focuses on the main characteristics of the educational methods applied in training programs in the nursing process or nursing care plan. The original studies were extracted from the PubMed, ProQuest, Scopus, Science Direct and, Web of Science databases, following two-step screening by two reviewers. Accordingly, 21 papers were included in the study based on inclusion criteria. According to the results, 42.85% of educational methods were computer-based while 57.15% were non-computer based. Computers were used as the main educator (14.28%) or as an assisted-tool (25.57%). The lecture-based training, as one of the non-computer based educational tools, was the most frequent method observed across the studies (33.3%). There are two frequently used measures of evaluating the educational programs learner's knowledge of nursing process (28.75%) and their attitude toward the program (23.80%). The results suggested that in order to improve educational methods for the nursing process, computers, mobile phones, and other available technologies should be integrated with the traditional educational methods. Also, comprehensive measures should be applied for evaluating them.