A Systematic Review of Health Management Mobile Applications in COVID-19 Pandemic: Features, Advantages, and Disadvantages.

Introduction: With the increasing accessibility of smartphones, their use has been considered in healthcare services. Mobile applications have played a pivotal role in providing health services during COVID-19. This study is aimed at identifying the features, advantages, and disadvantages of health management mobile applications during COVID-19. Methods: This systematic review was conducted in PubMed, Scopus, and Web of Science using the related keywords up to November 2021. The original articles in English about the health management mobile applications in COVID-19 were selected. The study selection was done by two researchers independently according to inclusion and exclusion criteria. Data extraction was done using a data extraction form, and the results were summarized and reported in related tables and figures. Results: Finally, 12 articles were included based on the criteria. The benefits of mobile health applications for health management during COVID-19 were in four themes and 19 subthemes, and the most advantages of the application were in disease management and the possibility of recording information by users, digital tracking of calls, and data confidentiality. Furthermore, the disadvantages of them have been presented in two themes and 14 subthemes. The most common disadvantages are reduced adherence to daily symptom reports, personal interpretation of questions, and result bias. Conclusion: The study results showed that mobile applications have been effective in controlling the prevalence of COVID-19 by identifying virus-infested environments, identifying and monitoring infected people, controlling social distancing, and maintaining quarantine. It is suggested that usability, ethical and security considerations, protection of personal information, and privacy of users be considered in application design and development.

Non-fungible tokens in healthcare: a scoping review.

Introduction: Non-Fungible Tokens (NFTs) are digital assets that are verified using blockchain technology to ensure authenticity and ownership. NFTs have the potential to revolutionize healthcare by addressing various issues in the industry. Method: The goal of this study was to identify the applications of NFTs in healthcare. Our scoping review was conducted in 2023. We searched the Scopus, IEEE, PubMed, Web of Science, Science Direct, and Cochrane scientific databases using related keywords. The article selection process was based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Results: After applying inclusion and exclusion criteria, a total of 13 articles were chosen. Then extracted data was summarized and reported. The most common application of NFTs in healthcare was found to be in health data management with 46% frequency, followed by supply chain management with 31% frequency. Furthermore, Ethereum is the main blockchain platform that is applied in NFTs in healthcare with 70%. Discussion: The findings from this review indicate that the NFTs that are currently used in healthcare could transform it. Also, it appears that researchers have not yet investigated the numerous potentials uses of NFTs in the healthcare field, which could be utilized in the future.

The effect of using mobile health on self-management of type 2 diabetic patients: A systematic review in Iran.

Type 2 diabetes, as one of the most common chronic diseases, requires ongoing management and support from the patient; therefore, patient participation and self-management play a pivotal role in controlling and preventing this disease. The increasing use of smartphones has provided a good opportunity for controlling and managing patients with type 2 diabetes. This study aimed to investigate the effect of mobile health on the self-management of patients with type 2 diabetes in Iran. A systematic review study was conducted from 2010 to 2021. Searches in Persian and English scientific databases, IranDoc, MagIran, SID Web of science, and PubMed, were performed using keywords such as diabetes and mobile health. The process of reviewing and selecting articles based on inclusion and exclusion criteria was performed by two researchers independently. The study evaluation was performed by using a standard tool. After selecting articles, data extraction was performed using a data extraction form. Data analysis was performed with a content analysis approach. Finally, 23 articles were included from the 7767 articles found in the initial search stage, which examined patients' self-care in 11 areas using mobile health. Fourteen studies (61%) considered mobile health to be effective in increasing hemoglobin control. Other studies also found the use of mobile health in increasing adherence to exercise (n = 10), increasing adherence to medication (n = 9), increasing adherence to diet (n = 11), increasing care for diabetic foot ulcers (n = 8), increasing self-efficacy and empowerment (n = 5), increasing cholesterol control (n = 4), increasing awareness and attitude (n = 4), increasing control of insulin dose (n = 2), increasing adherence to education (n = 1), and increasing control of blood urea (n = 1), which were considered effective. The use of m-health effectively controls the disease and promotes self-management in type 2 diabetic patients. Considering the high cost of diabetes treatment, policymakers should implement appropriate interventions and strategies in the field of using mobile health to improve adherence to self-management of the disease.

Mobile health interventions for cancer patient education: A scoping review.

INTRODUCTION: Mobile health (mHealth) is using mobile devices and applications to deliver health information and services. mHealth has been increasingly applied in cancer care to support patients in various aspects of their disease journey. This scoping review aimed to explore the current evidence on the use of mHealth interventions for cancer patient education. METHODS: This scoping review followed the Joanna Briggs Institute (JBI) methodology for scoping reviews. We searched four electronic databases (PubMed, Web of Science, CINAHL, and Cochrane) using a combination of keywords related to mHealth, cancer, and education. After finding articles at the initial search the screening has been done based on the inclusion and exclusion criteria. We included only original research articles and excluded all other types of publications, such as review papers, reports, editorials, letters to the editor, book reviews, short communications, conference proceedings, graduate dissertations, protocols, and commentaries. We extracted data on the characteristics and outcomes of the included studies using a standardized form. We conducted a narrative synthesis and inductive content analysis to summarize and categorize the evidence. RESULTS: Out of 2131 records found in the initial search, 28 full-text articles reported on the use of mHealth educational interventions for cancer patients. The majority of the studies focused on breast cancer patients (n = 21, 75%). The most common type of mHealth intervention was exercise-based education delivered through various media such as text messages, videos, audio, images, and social networks. The main objectives of mHealth educational interventions were to enhance self-management skills, improve psychological well-being, and promote healthy lifestyle behaviors among cancer patients. The reported outcomes of mHealth interventions included reduced chemotherapy-related side effects, improved mental health, improved quality of life and lifestyle, and better pain management. CONCLUSION: This scoping review showed that mHealth is a promising and feasible modality for delivering educational interventions to cancer patients. However, more rigorous and diverse studies are needed to evaluate the effectiveness and cost-effectiveness of mHealth interventions for different types of cancers, stages, and settings.

Features of teleoncology in lung cancer: A scoping review.

OBJECTIVES: There are several challenges in providing healthcare services for lung cancer patients. Using teleoncology is an effective solution to meet such challenges. Given this, we in this study aimed to identify the features of teleoncology in lung cancer. METHODS: We conducted this scoping review in 2023. We first searched scientific databases including PubMed, Scopus, ISI Web of Sciences, and Science Direct by combining related keywords for the past 12 years (2012-2023). RESULTS: After reviewing 860 articles, we selected 39 studies for the purpose of this study. The interventions of teleoncology for lung cancer patients have four main categories, namely: monitoring of symptoms, monitoring the process of treatment and rehabilitation of patients, self-management and patient empowerment, and providing consultation for patients. CONCLUSION: The appropriate implementation of teleoncology systems improves the patient's condition and reduces lung cancer complications by improving the availability of different health services. PRACTICE IMPLICATIONS: More attention should be paid to the evaluation of telemedicine systems from the perspective of patients and health service providers. Also, the latest platforms, including mobile phone-based software, should be used to implement such systems.

Telemedicine in cancer care during COVID-19 pandemic: a systematic mapping study.

Background: For monitoring, providing, and managing COVID-19 pandemic healthcare services, telemedicine holds incredible potential. During this period, there has been a change in the remote services offered to cancer patients. As a result, the purpose of this study was to conduct a mapping review to identify and classify telemedicine applications for providing cancer care to patients during the COVID-19 pandemic. Methods: Articles published in scientific databases such as Web of Science, Scopus, PubMed, and ProQuest up to 2022 were searched for in this systematic mapping study. Identifying keywords, creating a search strategy, and selecting data sources were all part of our search for relevant articles. The articles were chosen in phases based on inclusion and exclusion criteria. Results: A total of 1331 articles were found, with the majority of them (46% of them) taking place in the United States. Telemedicine systems were most commonly developed for breast cancer (11.4%), lung cancer (7.9%), head and neck cancer (6.4%), brain cancer (5.4%), gynecologic cancer (6.0%), urological cancer (5.7%), prostate cancer (5.0%), colorectal cancer (5.0%), biliary tract cancer (5.0%), and skin cancer (5.0%). Teleconsultation was the most common type of telemedicine application, with 60% of it taking place in real time. Conclusion: Because of its emphasis on providing high-quality health care while reducing costs, telemedicine has gained popularity in the majority of countries, with positive economic and social consequences. While telemedicine systems provide a variety of healthcare services, during the COVID-19 era, they do not currently provide many services to all cancer patients worldwide. Supplementary Information: The online version contains supplementary material available at 10.1007/s12553-023-00762-2.

Design and Development of a Hospital-Based Coronary Artery Disease (CAD) Registry in Iran.

Background: The incidence of coronary artery disease (CAD), the leading cause of mortality in most developed and developing countries, is increasing. The adoption of hospital registries can improve care delivery and facilitate the management of CAD through better planning, as well as help with outcome assessment through more effective data management. Objectives: The present study is aimed at designing a hospital-based CAD registry for managing CAD data. Methods: This developmental study was conducted in three phases. Initially, sources related to CAD registries were reviewed, the results of which were published in two studies. In the next phase, the prerequisites and requisites of the software were determined through a qualitative study. In this phase, the registry dataset was determined by using a questionnaire. Finally, the developed conceptual model of the software was validated. The software was then developed based on the validated conceptual model. Results: The registry data elements were classified into 13 main categories, including identification data, medical history, and risk factors. The dataset included 171 data elements, including data related to surgical and nonsurgical procedures. The conceptual model was approved by field experts, and the software was developed accordingly. Conclusion: The steps followed in the present study for developing the CAD registry can be used as an appropriate approach for designing similar hospital-based registries. Considering the pivotal role of the registry in the management of CAD, the routine and systemic use of the registry is suggested in all healthcare centers.

Designing and Evaluating a Nutrition Recommender System for Improving Food Security in a Developing Country.

BACKGROUND: Due to the increased price of foods in recent years and the diminished food security in Iran, nutrition recommender systems can suggest the most suitable and affordable foods and diets to users based on their health status and food preferences. Objective: The present study aimed to design and evaluate a recommender system to suggest healthy and affordable meals and provide a tele-nutrition consulting service. METHODS: This applied three-phase study was conducted in 2020. In the first stage, the food items' daily prices were extracted from credible sources, and accordingly, meals were placed in three price categories. After conducting a systematic review of similar systems, the requirements and data elements were specified and confirmed by 10 nutritionists and 10 health information management and medical informatics experts. In the second phase, the software was designed and developed based on the findings. In the third phase, system usability was evaluated by four experts based on Nielsen's heuristic evaluation. RESULTS: Initially, 72 meals complying with nutritional principles were placed in three price categories. Following a literature review and expert survey, 31 data elements were specified for the system, and the experts confirmed system requirements. Based on the information collected in the previous stage, the Web-based software TanSa in the Persian language was designed, developed, and presented on a unique domain. During the evaluation, the mean severity of the problems associated with Nielsen's 10 principles was 1.2, which is regarded as minor. CONCLUSION: To promote food security, the designed system recommends healthy, nutritional, and affordable meals to individuals and households based on user characteristics.

Assessing the e-health literacy level and its predictors in heart patients: A Case Study in a Heart Hospital Center in Iran.

BACKGROUND: eHealth literacy has many benefits for patients and community members, including the direct impact on improving the quality of patient education and reducing direct and indirect healthcare costs. Benefiting from eHealth literacy in patients with cardiovascular diseases can effectively provide healthcare services and manage these patients. This study aimed to evaluate eHealth literacy level and its factors affecting patients with cardiovascular diseases in a Heart Center Hospital. MATERIALS AND METHODS: This cross-sectional study was conducted in 2022. A valid and reliable questionnaire has been used for data gathering. From 147 distributed questionnaires among patients with cardiovascular diseases at Madani Heart Center Hospital in Khorramabad city, finally, 86 questionnaires have been collected completely. Data analyses were done using IBM Statistical Package for the Social Sciences (SPSS) software version 22 descriptive and analytical tests such as one-way ANOVA, independent sample t-test, and Spearman correlation coefficient based on the study objectives. RESULTS: The study showed that heart patients' eHealth literacy status is moderate (3.38 out of 5). The awareness of the availability of resources on the Internet had the highest score (3.79). The importance of using the Internet to obtain health information (r = 0.62, P < 0.001) and the ability to use the Internet (r = 0.62, P < 0.001) had the most significant relationship with eHealth literacy among patients with cardiovascular diseases. CONCLUSION: It is suggested that by increasing the level of Internet skills, expanding the use of the Internet for health-related services, using the Internet to make accurate health decisions among patients, extending the use of the Internet to access health resources, and reducing the patient's level of concern about their health status to improve the level of eHealth literacy of cardiovascular patients.

Telemedicine in lung cancer during COVID-19 outbreak: A scoping review.

The coronavirus disease 2019 (COVID-19) pandemic has negatively affected the medical services, particularly cancer diagnosis and treatment, for vulnerable cancer patients. Although lung cancer has a high mortality rate, monitoring and following up of these patients can help to improve disease management during the pandemic. Telemedicine has proven to be an effective method of providing health care to these patients. As a result, the purpose of this study was to identify telemedicine applications in the management of lung cancer patients during the COVID-19 pandemic. In this scoping review, studies published in online scientific databases such as Web of Science, Scopus, and PubMed between January 1, 2020 and September 1, 2021 were systematically searched and screened. The studies were chosen using predetermined inclusion and exclusion criteria. The bibliometric information and technological aspects of included studies were collected using a data extraction form and the data was analyzed using the content analysis approach. A total of 68 articles were found, from which four articles were finally selected based on specific inclusion/exclusion criteria. Real-time consultation was one of the most common applications of telemedicine to deliver health-care services to cancer patients. Health-care providers used applications such as Zoom, Facetime, WeChat, and e-mail, as well as devices including PCs, phones, and smartphones to provide real-time consultation to patients via videoconferencing, phone calls, and messaging, as well as store and forward consultation via e-mail. Telemedicine in the COVID-19 pandemic provides health-care services to lung cancer patients at their homes by enabling physicians and patients to communicate in real time. Several telemedicine services are still unavailable for patients with lung cancer. As a result, health experts, politicians, and entrepreneurs must pay special attention to this issue.

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.

Advantages and disadvantages of teleworking in healthcare institutions during COVID-19: A systematic review.

Introduction: The prevalence of COVID-19 as pandemic disease and efforts to control it have caused extensive changes in work methods and the global growth of teleworking, especially in health. This study aimed to investigate the advantages and disadvantages of teleworking in healthcare institutions during the Covid-19 era. Methods: This systematic review was conducted up to January 1, 2022, by searching the relevant keywords in PubMed, Scopus, Web of Science, and ProQuest databases. Study selection has been conducted based on inclusion and exclusion criteria. Data extraction was done using the data extraction form based on the study objectives. Results: From all 276 articles retrieved, 14 studies were included in the study. The results show that England had the highest number of articles (6 articles). The advantages of teleworking have ten categories, and the disadvantages have nine categories. The most important benefits of teleworking include facilitating service delivery, increasing satisfaction, supporting healthcare providers, and reducing costs. The most important disadvantages of using teleworking have been the lack of facilities and support, the lack of technology acceptance, and reduced interactions between healthcare providers. Conclusion: Although teleworking was a suitable solution for some problems in healthcare institutions during COVID-19, it is also associated with obstacles. It is recommended that managers make policies and guidelines to use appropriate technologies, provide facilities, and have continuous support and increased interactions between healthcare providers and patients.

Efficient Model for Coronary Artery Disease Diagnosis: A Comparative Study of Several Machine Learning Algorithms.

Background: In today's industrialized world, coronary artery disease (CAD) is one of the leading causes of death, and early detection and timely intervention can prevent many of its complications and eliminate or reduce the resulting mortality. Machine learning (ML) methods as one of the cutting-edge technologies can be used as a suitable solution in diagnosing this disease. Methods: In this study, different ML algorithms' performances were compared for their effectiveness in developing a model for early CAD diagnosis based on clinical examination features. This applied descriptive study was conducted on 303 records and overall 26 features, of which 26 were selected as the target features with the advice of several clinical experts. In order to provide a diagnostic model for CAD, we ran most of the most critical classification algorithms, including Multilayer Perceptron (MLP), Support Vector Machine (SVM), Logistic Regression (LR), J48, Random Forest (RF), K-Nearest Neighborhood (KNN), and Naive Bayes (NB). Seven different classification algorithms with 26 predictive features were tested to cover all feature space and reduce model error, and the most efficient algorithms were identified by comparison of the results. Results: Based on the compared performance metrics, SVM (AUC = 0.88, F-measure = 0.88, ROC = 0.85), and RF (AUC = 0.87, F-measure = 0.87, ROC = 0.91) were the most effective ML algorithms. Among the algorithms, the KNN algorithm had the lowest efficiency (AUC = 0.81, F-measure = 0.81, ROC = 0.77). In the diagnosis of coronary artery disease, machine learning algorithms have played an important role. Proposed ML models can provide practical, cost-effective, and valuable support to doctors in making decisions according to a good prediction. Discussion. It can become the basis for developing clinical decision support systems. SVM and RF algorithms had the highest efficiency and could diagnose CAD based on patient examination data. It is suggested that further studies be performed using these algorithms to diagnose coronary artery disease to obtain more accurate results.

The Virtual Reality Technology Effects and Features in Cardiology Interventions Training: A Scoping Review.

Background: Virtual Reality (VR) as an emerging and developing technology has received much attention in healthcare and trained different medical groups. Implementing specialized training in cardiac surgery is one of the riskiest and most sensitive issues related to clinical training. Studies have been conducted to train cardiac residents using this technology. This study aimed to identify the effects and features of VR technology in cardiology interventions training. Methods: This scoping review was conducted in 2021 by searching PubMed, Scopus, and Web of Sciences scientific databases by combining the related keywords. A data extraction form was used for data gathering. Data analyses were done through the content analysis method, and results were reported based on the study objectives. Results: 21 studies were included; from the 777 articles found in the initial searches, seven (33.33%) were RCT studies. VR-based education studies in cardiology interventions have grown significantly in recent years. The main effects of applying VR include improved user attitude and satisfaction, improved performance after VR training, and improved training and learning. Input devices include tracking devices, point input devices, and controllers. Output devices were three main categories include graphics audios and haptic. Conclusion: The use of new technologies, especially VR, can improve the efficiency of medical training in clinical settings. It recommends that this technology train the necessary skills for heart surgery in cardiac residents before performing real surgery to reduce the potential risks and medical errors.

Assessing the online search behavior for COVID-19 outbreak: Evidence from Iran.

INTRODUCTION: Google Trends (GT) is an important free tool for online search behavior analysis, which provides access to Internet search patterns in Google. In recent decades, this database has been used for predicting the outbreak of epidemics and pandemics in different regions of the world. The present study aimed to evaluate Iranian users' COVID-19-related online search behavior. METHODS: This longitudinal study was conducted in 2021. The data of Iranian users' COVID-19-related online search behavior (trend) were collected from the GT website, and the epidemiological data of the COVID-19 outbreak in Iran from 16 February 2020 to 2 January 2021 were sourced from the Iranian ministry of health and medical education, as well as the World Health Organization. The data were analyzed in SPSS using descriptive and inferential statistics. RESULTS: All the COVID-19-related search terms in Iran gained their highest popularity value (relative search volume = 100) in the first 8 weeks of the pandemic, and then this value assumed a decreasing trend over time. Based on factor analysis, relative search volume (RSV) of factor 1 terms (related to corona [in Persian] and corona) have a low significance relationship with COVID-19 epidemiological data in one-, two-, and three-week time lags. Although, RSV of factor 2 terms (related to COVID [in Persian], COVID-19, and coronavirus) correlated with the total weekly number of COVID-19 cases in mentioned time lags. CONCLUSION: COVID-19-related search terms were popular among Iranian users at the beginning of the pandemic. The online search queries and the key terms searched by Iranian users varied during the COVID-19 pandemic. This study provides evidence in favor of the adoption of GT as an epidemiological surveillance tool but, it is necessary to consider that mass media and other confounders can significantly influence RSVs.

Developing a Multifaceted Evaluation Tool for Electronic Prescribing System: A Study from a Developing Country.

Evaluation of electronic prescribing systems (EPS) can contribute to their quality assurance, and motivate users and policy-makers to implement these systems, directly influencing the health of society. An appropriate evaluation tool plays a determining role in the identification of proper EPS. The present study aimed to develop a multifaceted evaluation tool for assessing the EPS. This study was conducted in two main steps in 2018. In the first step, we conducted a literature review to find the main features and capabilities of the prosperous EPS. In the second step, a Delphi method was used for determining the final criteria for evaluating EPS. After preparing a primary questionnaire based on the first step results, 27 expert stakeholders from related fields participated in this 3-phase Delphi study. The narrative content analysis and descriptive statistics were used for data analysis. The final evaluation tool consists of 61 questions in 10 main dimensions, including practical capabilities of the process/user and patient safety, data storage and transfer, prescription control and renewal, technical functions, user interfaces, security and privacy, reporting, portability, hardware and infrastructure, and system failure/recovery. The evaluation tool developed in this study can be used for the critical appraisal of features of EPS. It is recommended that this multifaceted evaluation tool be employed to help buyers compare different systems and assist EPS software vendors in prioritizing their activities regarding the system development. By using this tool, healthcare organizations can also choose a system that improves many aspects of health care.

The attributes of hospital-based coronary artery diseases registries with a focus on key registry processes: A systematic review.

BACKGROUND: The management of data on coronary artery disease (CAD) plays a significant role in controlling the disease and reducing the mortality of patients. The diseases registries facilitate the management of data. OBJECTIVE: This study aimed to identify the attributes of hospital-based CAD registries with a focus on key registry processes. METHOD: In this systematic review, we searched for studies published between 2000 and 2019 in PubMed, Scopus, EMBASE and ISI Web of Knowledge. The search terms included coronary artery disease, registry and data management (MeSH terms) at November 2019. Data gathering was conducted using a data extraction form, and the content of selected studies was analysed with respect to key registry processes, including case finding, data gathering, data abstracting, data quality control, reporting and patient follow-up. RESULTS: A total of 17,604 studies were identified in the search, 55 of which were relevant studies that addressed the 21 registries and were selected for the analysis. Results showed that the most common resources for case finding included admission and discharge documents, physician's reports and screening results. Patient follow-up was mainly performed through direct visits or via telephone calls. The key attributes used for checking the data quality included data accuracy, completeness and definition. CONCLUSION: CAD registries aim to facilitate the assessment of health services provided to patients. Putting the key registry processes in place is crucial for developing and implementing the CAD registry. The data quality control, as a CAD registry process, requires developing standard tools and applying appropriate data quality attributes. IMPLICATIONS: The findings of the current study could lay the foundation for successful design and development of CAD registries based on the key registry processes for effective data management.

The Features of Mobile-Based Software in Self-Management of Patients with Asthma: A Review Article.

BACKGROUND: The use of mobile-based software for the self-management of patients with asthma improves the quality of life, reduces healthcare costs, provides effective health care interventions in asthma, and supports the patients in self-management. The current study was performed to identify the features of mobile-based self-management software for patients with asthma (MSSPA). MATERIALS AND METHODS: The present review study was performed in 2018. Four databases including PubMed, Scopus, Emerald, and Google Scholar were screened by the combination of selected keywords. Data were collected using a data extraction form. Data were analyzed using the content analysis method. Results were abstracted and reported based on the study objectives. RESULTS: Of the 297 articles retrieved during the first round of search, 24 were selected; 15 of which were the original articles (62.5%). As the most important applications of MSSPA, it could be used as a tool to support patients in self-management, provide them with educational information, and self-observation. Also, 75% of the studies (n=18) emphasized the effectiveness of MSSPA. Identification of the required field of the software was the most important requirement in using MSSPA. Nevertheless, some of the studies reported the low quality and compatibility of some designed apps compared with those of the available information systems. CONCLUSION: Identification of MSSPA features and considering them in new versions can promote the quality of MSSPA. However, according to the results of the study, in addition to identifying the software features, more attention should be paid to the users' needs in software design.

Factors Affecting the Acceptance of Mobile Health by Medical Sciences Students: A Cross-Sectional Study.

BACKGROUND: The use of mobile health has a pivotal role in the prevention and treatment of many diseases. This study aimed at determining the affecting factors in acceptance of mobile health by using a modified acceptance model, among medical sciences students in the south-west of Iran. MATERIALS AND METHODS: This cross-sectional, analytical study was conducted in 2017. The research population included all the students of Lorestan University of Medical Sciences (LUMS). The 352 of students selected as the samples of study through a stratified sampling method. Data gathering was done through a valid and reliable questionnaire. The data was analyzed using Linear Structural Relations (LISREL) and Statistical Package for the Social Sciences (SPSS) software. RESULTS: The findings showed that perceived usefulness (t7, 38= 2.16, p = 0.03), performance expectancy (t7, 70= 3.18, p = 0.01), facilitating conditions (t10, 61= 4.17, p < 0.001), and attitude to use (t7, 14= 5.49, p < 0.001) were effective in the behavior intention of mobile health. Moreover, the results showed that the behavior intention of mobile health applications (t10, 77= 8.10, p < 0.001) is effective on its user behavior. CONCLUSIONS: The results of our study showed that perceived usefulness, performance expectancy, facilitating conditions, and attitude to use of technology were the affecting factors in the acceptance of mobile health by the students. It is suggested that the policymakers and authorities comprehensively consider these important factors when introducing new technologies.