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.

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.

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.

Capabilities and Advantages of Cloud Computing in the Implementation of Electronic Health Record.

BACKGROUND: With regard to the high cost of the Electronic Health Record (EHR), in recent years the use of new technologies, in particular cloud computing, has increased. The purpose of this study was to review systematically the studies conducted in the field of cloud computing. METHODS: The present study was a systematic review conducted in 2017. Search was performed in the Scopus, Web of Sciences, IEEE, Pub Med and Google Scholar databases by combination keywords. From the 431 article that selected at the first, after applying the inclusion and exclusion criteria, 27 articles were selected for surveyed. Data gathering was done by a self-made check list and was analyzed by content analysis method. RESULTS: The finding of this study showed that cloud computing is a very widespread technology. It includes domains such as cost, security and privacy, scalability, mutual performance and interoperability, implementation platform and independence of Cloud Computing, ability to search and exploration, reducing errors and improving the quality, structure, flexibility and sharing ability. It will be effective for electronic health record. CONCLUSION: According to the findings of the present study, higher capabilities of cloud computing are useful in implementing EHR in a variety of contexts. It also provides wide opportunities for managers, analysts and providers of health information systems. Considering the advantages and domains of cloud computing in the establishment of HER, it is recommended to use this technology.