Supporting Cancer Patients in Illness Management: Usability Evaluation of a Mobile App

BackgroundGiven the effective role of a mobile applications in disease management, disease monitoring, and self-care in patients with COVID-19 disease, we aimed to design, development and evaluation of a self-care Mobile app for COVID-19 patients not requiring hospitalization.MethodsThe design, development and evaluation the usability of the self-care and education mobile app for patients with COVID-19 disease were conducted in two main phases at 2021 in Northwest of IRAN; (1) Determine the features and capabilities and (2) Design, development and evaluation of self-care mobile App. JAVA programming languages and Android Operating System were used and selected to design and development of a mobile app. There were 25 participants who conducted evaluations of the mobile app’s usability and impact using the mobile health app usability a Questionnaire of User Interface Satisfaction was administered to assess the usability of the developed application. The results were analyzed via Excel 2013.ResultsThe model of developing a mobile app as an Information System was the Waterfall model. The smartphone application based on a set of capabilities and features was designed and consists of two main parts: the login screen for user registration, and the main home menu. The user interface includes three main pages or activities; (a) Main Menu for quick access to all of the pages, (b) Symptom management and monitoring to monitor the signs and symptoms during the illness, and (c) Set Reminders and Alarms to notify patients. The users’ mean score of the application usability was calculated as 7.91 out of 9 indicating a good level of satisfaction.ConclusionThis app can be a guideline and a useful tools for managing and monitoring symptoms, reminding medications, and implementing self-care instructions in outpatients. The authors suggest evaluating the efficacy and functionality test of mobile-based applications for COVID-19 in clinical trial studies.

Mobile phones are considered extremely crucial for their daily usage due to their unique features such as mobility, availability, and compatibility. Moreover, the need for mobile apps periodically increases in terms of the variety of end-users as well as mobile platforms. Iraq is an emerging country concerning the development and requirements of mobile apps. There are numerous challenges faced by this trend on mobile phone app requirements, development, and usage. Consequently, the major consideration is how to build a suitable mobile app that can be adopted, adapted, and customized according to Iraqi market requirements. An essential fact worth mentioning is the increase in unemployed computer departments alumni in Iraq. Those who can develop mobile apps and software need to recruit suitable candidates. The purpose of this article is to develop a customized flight booking mobile application to partially reduce and solve the problem of unemployed computer alumni. The target of this application is to reduce time and effort for passengers and offer unique features. The developed application is the adoption of previous applications and the improvement of their inadequacies. By following a six-phase methodology to set a procedural technique for optimizing the use of the mobile application as a source of revenue for unemployed alumni as well as being beneficial for the customer. The validation and verification of the proposed application of this current research are done by evaluating and executing the mobile application. The results of this paper meet the main objective, where, the special features have been implemented and tested. In addition, the application has been installed on mobile phones and tested. Furthermore, the income from this application is obtained through purchasing it or subscribing to it for a specific duration. We encourage researchers as well as alumni who are targeted in this field to be attentive to cutting-edge technology and advancement and the concept of this paper.

Cardiac arrest, acute myocardial infarction (AMI), and stroke affect millions of people in the United States annually.1 Despite significant advances in medical treatments for these conditions, they remain a major public health problem and a leading cause of morbidity and mortality.1 A critical common element in optimizing care and outcomes for these conditions is the timely recognition of symptoms and initiation of treatment. For example, rapid initiation of cardiopulmonary resuscitation (CPR) is associated with improved survival from cardiac arrest.2 Similarly, early recognition and presentation after onset of symptoms of AMI and ischemic stroke enable implementation of critical therapies such as primary angioplasty and thrombolysis, which are known to improve outcomes.1 Indeed, the “Chain of Survival” for emergency cardiovascular and cerebrovascular care (ECCC) starts with prompt identification of the condition and early activation of the healthcare system to rapidly initiate care.3 Unfortunately, despite national efforts that include public education initiatives and clinical practice guideline recommendations from entities such as the American Heart Association (AHA), major gaps remain in the timely identification of symptoms and initiation of ECCC.4–6 As one example, studies of out-of-hospital cardiac arrest (OHCA) have consistently noted delays in the initiation of bystander CPR.7 For AMI, there have been advances in the provision of timely primary angioplasty for ST-segment elevation myocardial infarction (STEMI), as reflected by significant improvements in door-to-balloon times.8 However, the time from patient symptom onset to seeking care for possible myocardial infarction has not improved significantly.9,10 Similarly, for stroke, there continue to be advances in door-to-needle times, but stroke symptom recognition and seeking of treatment by patients and their families remain a major barrier to timely stroke care.11–16 Public and clinician education efforts alone are not sufficient to reduce gaps …

This research is about the development, testing and application of mobile app for optimum location spot of a single facility. The approach is to use Center of Gravity Method to locate the central locations of the facility. This equality would reflect balance and minimum time and cost. The main variables to be considered in the systems are customer's distance, customer's demands and transportation rates. In general, firms which apply technologies will perform significantly better than those that do not. This leads to the development of a mobile app to identify best location for a single facility which will serve several demand centers. After the development of a mobile app, this undergoes testing which includes verification whether the mobile app will provide the same result in theoretical computations. The study confirms that the mobile app is consistent with the theoretical computations for location planning. This mobile app becomes a decision support system suggesting that they can access this mobile app to improve the firm's performance on decision making. A faster and effective decision making since instead of manual computation which will take time, the computation will be in a few seconds plus you could visualize the geographic areas being investigated. Moreover, the mobile app is practical to implement because it is flexible and easy to use. The data needed is easy to gather. The mobile app can generate up to 100 iterations to ensure that global maxima is obtained.

BackgroundA personal health record (PHR) system encourages patients to engage with their own health care by giving them the ability to manage and keep track of their own health data. Of the numerous PHR systems available in the market, many are Web-based patient portals and a few are mobile apps. They have mainly been created by hospitals and electronic health record (EHR) vendors. One major limitation of these hospital-created PHR systems is that patients can only view specific health data extracted from their EHR. Patients do not have the freedom to add important personal health data they collect in their daily lives into their PHR. Therefore, there is an information gap between clinical visits.ObjectiveThe aim of this study was to develop and evaluate a new mobile PHR app that can be easily used to manage various types of personal health data to fill the information gap.MethodsA user-centered approach was used to guide the development and evaluation of the new mobile PHR app. There were three steps in this study: needs assessment, app design and development, and conducting a usability study. First, a large-scale questionnaire study was conducted with the general population to gain an understanding of their needs and expectations with regard to a mobile PHR app. A mobile PHR app for personal medical data tracking and management was then created based on the results of the questionnaire study. End users were actively involved in all stages of the app development. Finally, a usability study was performed with participants to evaluate the usability of the mobile PHR app, which involved asking participants to finish a set of tasks and to respond to a usability questionnaire.ResultsIn the questionnaire study for needs assessment, there were 609 participants in total. The answers from these participants revealed that they wanted to manage various types of personal health data in a mobile PHR app. Participants also reported some features they desired to have in the app. On the basis of the needs assessment findings, a new mobile PHR app (PittPHR) was created with 6 major modules: health records, history, trackers, contacts, appointments, and resources. This app allows users to customize the trackers according to their needs. In the usability study, there were 15 participants. The usability study participants expressed satisfaction with the app and provided comments and suggestions for further development.ConclusionsThis new mobile PHR app provides options for users to manage a wide range of personal health data conveniently in one place. The app fills the information gap between clinical visits. The study results indicated that this new mobile PHR app meets the need of users and that users welcome this app.

Mobile apps are fast emerging as assistive learning platforms for pre-schoolers, as well as junior school students. In fact, not just the parents but also the junior-level teachers encourage children to use mobile learning apps due to its many benefits such as interactive, enjoyable and informal, etc. Needless to say, the advent of mobile apps must also equitable for students with learning difficulties to take advantage of the same learning opportunities as other students. Students with learning difficulties suffer from disabilities in language, information processing, etc. that prevent them from performing their academic tasks in the same manner as other students. It is crucial to realize the development of mobile learning apps for students with learning difficulties requires inclusive designs that make the apps usable for them. The paper presents an evaluation of a mobile appDisleksia Belajar, which developed for students with dyslexia in junior school to learn the Malay language. Dyslexia is a common learning difficulty that causes problems with language processing e.g. reading and writing. The evaluation is performed using SUS and Fun ToolKit (v3) techniques, which intend to explore the usability and engagement of the mobile app. There is a total of 12 students with dyslexia aged 7 to 12 years old recruited as the participants. The findings contribute towards understanding and improvement for the future development of mobile learning apps for students that having similar difficulty.

BackgroundThere is significant potential for mobile health technology to improve health outcomes for patients with chronic diseases. However, there is a need for further development of mobile health technology that would help to improve the health of lower-income communities.ObjectiveThe study objective was to assess mobile phone and app usage among a culturally diverse patient population, and to determine whether patients would be interested in using mobile health technology to help manage their chronic diseases.MethodsAn observational study was conducted with patients of the Internal Medicine resident primary care clinics of Los Angeles County and University of Southern California (LAC+USC) Medical Center. Self-reported information regarding demographics, current mobile phone usage, current mobile health app and social media usage, barriers to using mobile phones or mobile health apps, and interest in using a mobile health app was collected.ResultsNinety-one percent of patients owned a mobile phone, with 76% (169/223) of these reporting having a mobile phone with Internet capability. Fifty-seven percent of subjects used mobile apps on their mobile phones, and 32% (41/130) of these used mobile apps related to their health. Eighty-six percent (207/241) of respondents voiced interest in using a mobile app to improve their health, and 40% (88/221) stated they would use such an app daily. Patients stated they would find the mobile health app most useful for nutrition, exercise, and obtaining general information on medical conditions.ConclusionsDespite the fact that the majority of our primary care patients were of lower socioeconomic status, they utilized mobile phones with Internet and mobile app capabilities to a great extent. There was substantial interest among our patients in using mobile health technology to both manage chronic disease and improve overall health. Given that cultural, educational, and socioeconomic disparities strongly correlate with higher rates of chronic diseases such as obesity, diabetes and hypertension, access to culturally relevant mobile health tools may empower patients in these populations to improve health outcomes.

Health literacy is critical for cancer patients as they must understand complex procedures or treatment options. Caregivers' health literacy also plays a crucial role in caring for cancer patients. Low health literacy is associated with low adherence to medications, poor health status, and increased health care costs. There is a growing interest in the use of mobile health applications (apps) to improve health literacy. Mobile health apps can empower underserved cancer patients and their caregivers by providing features or functionalities to enhance interactive patient-provider communication and to understand medical information more readily. Despite the potentiality of improving health literacy through mobile health apps, there exist several related concerns: no equal access to mobile technology, no familiarity or knowledge of using mobile health apps, and privacy and security concerns. These elements should be taken into account for health policy making and mobile apps design and development. Importantly, mobile apps should be developed with the goal of achieving a high range of user access by considering all health literacy level and various cultural and linguistic needs.

One of the challenges facing resource-constrained environments is the proliferation of smartphones, the lack of skills to develop mobile apps, the high cost of professional mobile app development and the fact that there are no interventions to change the tide. Both communities and businesses, particularly the small- to medium-scale businesses have had two options: a) to use generic apps which are often not customisable, or b) not to use the technology. Globally, there are two emerging phenomena: the citizen developers and the mobile app development platform (MADP) with little or no programming code. Neither the citizen developer nor MADP are new but they have reached levels of maturity at which their potential in resource constrained contexts makes logical sense. The potential lies in empowering ordinary citizens to design and develop mobile applications that address their specific needs without being constrained by the lack of technical skills. This chapter presents a model to empower citizen developers to acquire mobile app design and development skills to develop mobile apps with few or no code development platforms. The chapter explores an empathy-driven mobile app development (empathy-driven MAD). MADs are safe and fun, they are called ‘digital sandpits’. The empathy-driven MAD without code has been shown to enhance creativity within multi-disciplinary teams and allow members of such teams to act as citizen developers who rapidly build apps, obtain feedback from ‘clients’ (peers) thereby shifting the dispositions of both the citizen developer and their community (world). This chapter uses Gidden’s structuration theory and an empathy map to exploit both tacit and discursive knowledge in the design of mobile apps and then using low-cost no-code MADPs learn quickly about user needs and build useable apps for communities.

The increasing demand for mobile apps is out the current capability of mobile app developers. In addition, the growing trend in smartphone ownership and the time people spend on mobile apps has raised several opportunities and risks for users and developers. The average time everyday a user spend on smartphones to use mobile apps is more than two hours. The worldwide mobile app revenue increase is estimated to grow 33%, $19 billion. Three quarter of the time used on mobile apps is solely for using game and social networking apps. To provide more customized services and function to users, mobile apps need to access to personal information. However, 80% of mobile apps put people's information privacy at risk. There is a major gap in the literature about the privacy concerns of mobile device users in the context of mobile apps. This dissertation addresses one fundamental research question: how does individuals' privacy change in the context of mobile apps? More precisely, the focus of this dissertation is on information privacy role in individuals' and mobile app developers' protective behaviors. We investigate the information sensitivity level influence on mobile app developers' emphasis on privacy across mobile app categories. The results show information sensitivity level has a significant impact on developers' emphasis on secondary usage of information. Moreover, we analyze the privacy trade-off dynamism in using a new social networking app and how it could result in emotional attachment. Results show initial use and initial disclosure influence the privacy trade-off from pre-use to initial-use period. Finally, the effect of privacy concern and engagement on emotional attachment is demonstrated. This dissertation addresses one fundamental research question: how does individuals' privacy change in the context of mobile apps? More precisely, the focus of this dissertation is on information privacy role in individuals' and mobile app developers' protective behaviors. We investigate the information sensitivity level influence on mobile app developers' emphasis on privacy across mobile app categories. The results show information sensitivity level has a significant impact on developers' emphasis on secondary usage of information. Moreover, we analyze the privacy trade-off dynamism in using a new social networking app and how it could result in emotional attachment. Results show initial use and initial disclosure influence the privacy trade-off from pre-use to initial-use period. Finally, the effect of privacy concern and engagement on emotional attachment is demonstrated.

Mobile medical apps (MMAs) work in close loop with human physiology through sensing and control. As such it is essential for them to achieve intended functionality, without having harmful effects on human physiology, affecting the availability of the service and compromising the privacy of health data. However for a mobile app manufacturer, generating evidences regarding safety, sustainability and security (S3) of MMAs can be time consuming. To accelerate the development of S3 assured MMAs, we propose Health-Dev β tool that takes high level description of MMAs and automatically generates validated code and evidences of safety, security, and sustainability. Using the mobile artificial pancreas medical control application we show that Health-Dev s tool can generate code that satisfies requirements and reduce development time by a factor of 1.8.

BackgroundThe use of mobile phones, and specifically smartphones, in the last decade has become more and more prevalent. The latest mobile phones are equipped with comprehensive features that can be used in health care, such as providing rapid access to up-to-date evidence-based information, provision of instant communications, and improvements in organization. The estimated number of health care apps for mobile phones is increasing tremendously, but previous research has highlighted the lack of critical appraisal of new apps. This lack of appraisal of apps has largely been due to the lack of clinicians with technical knowledge of how to create an evidence-based app.ObjectiveWe discuss two freely available methodologies for developing Web-based mobile phone apps: a website builder and an app builder. With these, users can program not just a Web-based app, but also integrate multimedia features within their app, without needing to know any programming language.MethodsWe present techniques for creating a mobile Web-based app using two well-established online mobile app websites. We illustrate how to integrate text-based content within the app, as well as integration of interactive videos and rich site summary (RSS) feed information. We will also briefly discuss how to integrate a simple questionnaire survey into the mobile-based app. A questionnaire survey was administered to students to collate their perceptions towards the app.ResultsThese two methodologies for developing apps have been used to convert an online electronic psychiatry textbook into two Web-based mobile phone apps for medical students rotating through psychiatry in Singapore. Since the inception of our mobile Web-based app, a total of 21,991 unique users have used the mobile app and online portal provided by WordPress, and another 717 users have accessed the app via a Web-based link. The user perspective survey results (n=185) showed that a high proportion of students valued the textbook and objective structured clinical examination videos featured in the app. A high proportion of students concurred that a self-designed mobile phone app would be helpful for psychiatry education.ConclusionsThese methodologies can enable busy clinicians to develop simple mobile Web-based apps for academic, educational, and research purposes, without any prior knowledge of programming. This will be beneficial for both clinicians and users at large, as there will then be more evidence-based mobile phone apps, or at least apps that have been appraised by a clinician.

In the last fifteen years, an immense expansion has been witnessed in mobile app usage and production. The intense competition in the tech sector and also the rapidly and constantly evolving user requirements have led to increased burden on mobile app creators. Nowadays, fulfilling users’ expectations cannot be readily achieved and new and unconventional approaches are needed to permit an interested crowd of users to contribute in the introduction of creative mobile apps. Indeed, users and developers of mobile apps are the most influential candidates to engage in any of the requirements engineering activities. The place where both can best be found is on Twitter, one of the most widely used social media platforms. More interestingly, Twitter is considered as a fertile ground for textual content generated by the crowd that can assist in building robust predictive classification models using machine learning (ML) and natural language processing (NLP) techniques. Therefore, in this study, we have built two classification models that can identify mobile apps users and developers using tweets. A thorough empirical comparison of different feature extraction techniques and machine learning classification algorithms were experimented with to find the best-performing mobile app user and developer classifiers. The results revealed that for mobile app user classification, the highest accuracy achieved was ≈0.86, produced via logistic regression (LR) using Term Frequency Inverse Document Frequency (TF-IDF) with N-gram (unigram, bigram and trigram), and the highest precision was ≈0.86, produced via LR using Bag-of-Words (BOW) with N-gram (unigram and bigram). On the other hand, for mobile app developer classification, the highest accuracy achieved was ≈0.87, produced by random forest (RF) using BOW with N-gram (unigram and bigram), and the highest precision was ≈0.88, produced by multi-layer perception neural network (MLP NN) using BERTweet for feature extraction. According to the results, we believe that the developed classification models are efficient and can assist in identifying mobile app users and developers from tweets. Moreover, we envision that our models can be harnessed as a crowd selection approach for crowdsourcing requirements engineering activities to enhance and design inventive and satisfying mobile apps.

Affinity and foreign users’ perception about Chinese mobile apps: An integrated view of affective contagion and value-based perspectives

Mobile Applications Development with Android: Technologies and Algorithms presents advanced techniques for mobile app development, and addresses recent developments in mobile technologies and wireless networks. The book covers advanced algorithms, embedded systems, novel mobile app architecture, and mobile cloud computing paradigms. Divided into three sections, the book explores three major dimensions in the current mobile app development domain. The first section describes mobile app design and development skills, including a quick start on using Java to run an Android application on a real phone. It also introduces 2D graphics and UI design, as well as multimedia in Android mobile apps. The second part of the book delves into advanced mobile app optimization, including an overview of mobile embedded systems and architecture. Data storage in Android, mobile optimization by dynamic programming, and mobile optimization by loop scheduling are also covered. The last section of the book looks at emerging technologies, including mobile cloud computing, advanced techniques using Big Data, and mobile Big Data storage. About the Authors Meikang Qiu is an Associate Professor of Computer Science at Pace University, and an adjunct professor at Columbia University. He is an IEEE/ACM Senior Member, as well as Chair of the IEEE STC (Special Technical Community) on Smart Computing. He is an Associate Editor of a dozen of journals including IEEE Transactions on Computers and IEEE Transactions on Cloud Computing. He has published 320+ peer-reviewed journal/conference papers and won 10+ Best Paper Awards. Wenyun Dai is pursuing his PhD at Pace University. His research interests include high performance computing, mobile data privacy, resource management optimization, cloud computing, and mobile networking. His paper about mobile app privacy has been published in IEEE Transactions on Computers. Keke Gai is pursuing his PhD at Pace University. He has published over 60 peer-reviewed journal or conference papers, and has received three IEEE Best Paper Awards. His research interests include cloud computing, cyber security, combinatorial optimization, business process modeling, enterprise architecture, and Internet computing. .