Analytical study of the COVID apps users’ perception about data security and privacy

COVID-19 pandemic has impacted many across the globe. Mobile tracing and exposure apps have been used to mitigate the problem and curb the spread of the virus. Wide exposure of the apps is in need for them to be effective. However, concerns about factors like data privacy and security affect users’ perception and participation in them. In this study, our goal is to investigate how information privacy and security may impact users’ ratings of COVID-19 apps. In addition, we explore how political typology also influences the ratings. We considered 31 apps related to COVID-19 exposure and tracing in the United States. From these apps, we managed to scrape data related to 29 from Google play digital store and extracted 1,832 reviews. After analyzing the user reviews our preliminary findings show that the polarity and subjectivity of the review are significantly associated with the reviewers’ apps ratings. Interestingly, we find this relationship intensifies when security and privacy issues are addressed in the reviews. In addition, we find that political ideology plays a significant role in how users rate COVID apps. The findings of this research have implications for both theory and practice

Online Video Reviews Helpfulness: Exploratory Study

Online reviews assist consumers in making an informed purchase decision and they became a trusted source for product information. This study aims to investigate online video reviews on YouTube to understand what are the most commonly reviewed products and what are the factors of YouTube video reviews which contribute to review helpfulness. We use qualitative and quantitative techniques as research methodologies. The results show that major categories reviewed on YouTube are video games, movies, and technology. Exploratory factor analysis revealed four important factors that may determine online video review helpfulness which are review popularity, comments, video information, and review depth. A conceptual model is introduced based on the factor analysis. The study has significant implications to research as it provides new insights regarding the role of online video reviews in purchases decision making process

Data Mining Algorithms Predicting Different Types of Cancer: Integrative Literature Review

Based on the World Health Organization, cancer is the second leading cause of death globally and is responsible for an estimated 9.6 million deaths in 2018. Globally, about 1 in 6 deaths is due to cancer, and approximately 70% of deaths from cancer occur in low and middle-income countries. with accelerating developments in technologies and the digitization of healthcare, a lot of cancer\u27s data have been collected, and multiple cancer repositories have been created as a result. cancer has become a data-intensive area of research over the last decade. A large number of researchers have used data mining algorithms in predicting different types of cancer to reduce the cost of tests used to predict different types of cancer, especially in low and middle-income countries. This paper reports on a systematic examination of the literature on data mining algorithms predicting different types of cancer through which we provide a thorough review, analysis, and synthesis of research published in the past 10 years. We follow the systematic literature review methodology to examine theories, problems, methodologies, and major findings of related studies on data mining algorithms predicting cancer that were published between 2009 and 2019. Using thematic analysis, we develop a research taxonomy that summarizes the main algorithms used in the existing research in the field, and we identify the most used data mining algorithms in predicting different types of cancer. In addition, to data mining algorithms used in predicting each type of cancer, as mentioned in the reviewed studies. We also identify the most popular types of cancer that researchers tackled using predictive analytics

Increasing the Effectiveness of Clinical Practices with Health Informatics: Systematic Literature Review

Healthcare informatics involves different areas and activities like data collection, data analysis, and knowledge sharing among health care professionals. Healthcare Informatics scholars have been contending that the advancement in the discipline can enable healthcare professionals to provide better care to patients and the public. The current study goal is to identify the effectiveness of health informatics in improving clinical nursing practice from recent literature. We followed the systematic literature review by reviewing research papers published in the period between 2009 until 2019. The extracted data showed that there are four main themes of the nursing practices that are affected positively by the implementation of healthcare informatics. Namely, they are promoting quality of healthcare, improving electronic documentation of nursing practice, improving technological competencies and leadership practices, and improving clinical decision making. We discuss the findings and identify gaps to better direct future research in this area

The factors that impact the adoption and Usage of Telemedicine in Chronic Diseases: Systematic Review

Chronic diseases are one of the most common diseases that pertain to a large number of people. Most people suffer from one or more chronic diseases, such as diabetes, heart failure, rheumatoid arthritis, cancer, and others. According to a recent statistic, 9% of Jordanian have at least one type of chronic disease; it is a high percentage for a country of limited resources. Chronic diseases are costly to manage; the cost is not only associated with the treatment alone but also to monitoring patients, healthcare professionals labor, and continuous lab testing. During the past few years, the world witnessed a significant increase in the number of mobile Health users. This increase also translated into an increase in using Telehealth services. This paper aims to conduct a systematic literature review of the different adoption factors of Telemedicine for chronic diseases. We provide an analysis and a synthesis of recently published research in the past ten years. We follow the methodological literature review proposed by Ramey and Rao to examine and extract related scholarly work. By providing a thematic analysis of relevant literature, we classify the current research into the main themes of the Telehealth in the chronic field. We also develop a taxonomy of positive and negative factors that influence Telehealth. We also highlight the main limitations and gaps in the literature to guide future research

The Impact of Speech Recognition Systems on The Productivity and The Workflow in Radiology Departments: A Systematic Review

Speech Recognition dictation systems are becoming more popular and provide a viable alternative to conventional transcription services. On the other hand, there is a scarcity in the studies that address the impact of speech recognition on productivity and the workflow in the radiology department. To review the most updated literature in the past 10 years regarding the effects of Speech Recognition systems on the productivity and workflow of radiology departments. A systematic literature review was done using PRISMA, including 14 articles in total, and they were divided into four main themes. The finding confirmed the positive effect of Speech Recognition on departmental productivity, with decreased report turnaround time and an increase in the number of reports available per unit of time

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Exploring the Effects of Information Security & Privacy on Blockchain Mobile Applications Rating: Text Analytics Approach

The widespread use of mobile technology has motivated Blockchain developers and users to embrace and adopt mobile blockchain technologies. Enabling users to utilize mobile devices for accessing blockchain services and manage digital assets that offer numerous benefits. However, risks regarding the system use and users’ concerns about their information security and privacy also arise. This paper investigates how blockchain apps’ perceived security and privacy levels affect the ratings of the app on online platforms. A dataset of 146 mobile apps that use Blockchain technology was collected to conduct a sentiment analysis for user reviews. Our results demonstrated that the perceived concerns of information security and privacy positively are associated with negative ratings of apps. We also investigate these effects by differentiating the apps according to the risk level of the app and showed that the magnitude of the effect is greater for high-risk apps

Impact of Knowledge Creation on Financial Performance: An Exploratory Study

Evaluation of the ability of a firm to create new knowledge and to succeed in its future research and development projects possess top interest for different parties such as investors, consultants, and board directors. Prior literature has suggested a relationship between knowledge creation and market value of a firm. In this study, we suggest a design science approach using data mining tools to build a model to explore the relationship between financial performance of a firm as reflected in financial statements and the success of knowledge creation represented in patent success. To achieve this objective, we use clustering analysis, attribute evaluation, and classification algorithms. Our data comprises of 2,500 firm year financial data encompassing 10 accounting measures. Utilizing the design science paradigm and business analytics tools to examine the relationship between financial performance and knowledge creation will have significant implications for theory and practice

The Role of Effectiveness, Appeal and Functionality on Evaluation of Health Apps

Mobile health applications (apps) are enabling health care service delivery through access to patients beyond service walls. A number of apps have emerged that help patients regarding information on diseases, treatment regimes, and taking informed decisions on health management. To sustain an app in the market, questions such as what functionalities influence a patient’s decision to use and evaluate the apps needs to be answered. A benchmark for sustained app use is the impact that the current evaluation has on the decision of the future users. This study explores the differential impact of effectiveness of health apps on patient evaluation change per week. Further, how the relationship between effectiveness and evaluation change differs across different app-functionalities and service appeal are explored. A dataset of 2,292 apps were used to conduct empirical analysis. We find that patients evaluate certain functionalities higher than others. Managerial and research contributions are also discussed