A developed mobile application for optimum facility location using center of gravity approach

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.

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 implementation of system development methodologies (SDMs) in mobile applications (mobile apps) development has a positive effect on companies and their respective software projects. SDMs provide a framework for planning, executing, and managing the process of developing software systems. In this paper, we investigate the worthiness of using of SDMs in the development of mobile applications. A survey was conducted among software developers in various organizations. The organizations included software development companies, financial institutions, telecommunication companies, engineering companies and educational institutions. A total of 152 out of 392 questionnaires distributed, were returned, giving a response rate of 38.8%. Furthermore, the responses were categorized into two groups (users/non-users of SDMs) and T-test analysis was performed to determine the differences between the means of the two groups. The findings indicate that SDMs are effectively used in developing mobile apps and there are significant practical differences between the users and non-users of SDMs in mobile apps development in areas of organizational size, the number of developers in the organization, years of experience, the number of applications developed and application success. The users (companies and individuals) are larger, more experienced and more productive. Furthermore, the use of SDMs in mobile apps development leads to more successful mobile apps. We conclude that SDMs are indeed worthy of use in mobile apps development.

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 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. .

The development of mobile apps, which are either suitably adapted or especially designed for use by sensory-deprived people, have contributed significantly to the continuously increasing adoption of digital assistive technologies by people with disabilities. Throughout the design of two assistive navigation mobile apps for blind and visually impaired people (BVI), a set of everyday practices and psychological features of the BVIs with respect to the use of mobile technology was identified. Specifically, interviews with BVIs were held at the first stage of the design process. The analysis of the responses revealed that appropriate training of a BVI on how to use these apps plays significant role on the anticipated app adoption and use rate. This study presents the everyday practices and psychological features of the BVIs, as they were inferred from the analysis of the interviews. It is argued that these psychological features and practices must be considered in the development of training practices concerning the use of the proposed technology. Towards this direction, a framework for the adequate training of BVIs on the use of assistive mobile apps is presented. Consideration of this framework during the development of assistive mobile apps for BVIs could contribute towards higher adoption rates.

Heart failure requires complex and daily self-care that many patients struggle with for a range of reasons including limited health literacy, cognitive impairment, comorbidities, and emotional distress. This study describes the user-centred design and development of a mobile app (SmartHeart) to support comprehensive self-monitoring and improve self-care engagement for people with heart failure. Building on previous co-design research and expert panel feedback, we developed an initial Figma prototype following user-centred design principles. Two online sessions were conducted with adults living with heart failure (n=7), including a focus group session and a follow-up individual feedback session. The same participants took part in both sessions to provide feedback on the functionality, aesthetics, navigation, and content. Data were analysed deductively based on heuristic principles of user interface design, with findings informing the iterative development of the SmartHeart mobile app. The functional app was tested in-home by two participants over two weeks to evaluate real-world usability and gather contextual feedback to inform further refinement. The SmartHeart prototype was developed through expert workshops and user feedback. Participants emphasised simplicity, leading to a streamlined design with clear navigation, adaptable graphics, and larger fonts. The app's health tracking features were iteratively improved. User-driven modifications included personalised threshold alerts, simplified symptom reporting, and integrated medication reminders. Participants reported high satisfaction with the prototype interface and health monitoring capabilities; however, formative testing identified reliability issues that are being addressed prior to pilot evaluation. Findings primarily inform design refinements before evaluating clinical effectiveness. The SmartHeart app was refined through user-centred design process involving direct feedback from individuals with heart failure, resulting in a self-care tool with user-friendly features, to be further evaluated in future research. These user-driven enhancements support self-care engagement and highlight the app's potential for real-world use and broader clinical integration.

BackgroundMobile phones and tablets currently represent a significant presence in people’s everyday lives. They enable access to different information and services independent of current place and time. Such widespread connectivity offers significant potential in different app areas including health care.ObjectiveOur goal was to evaluate the usability of the Connect Mobile app. The mobile app enables mobile access to the Connect system, an online system that supports cancer patients in managing health-related issues. Along with symptom management, the system promotes better patient-provider communication, collaboration, and shared decision making. The Connect Mobile app enables access to the Connect system over both mobile phones and tablets.MethodsThe study consisted of usability tests of a high fidelity prototype with 7 cancer patients where the objectives were to identify existing design and functionality issues and to provide patients with a real look-and-feel of the mobile system. In addition, we conducted semistructured interviews to obtain participants’ feedback about app usefulness, identify the need for new system features and design requirements, and measure the acceptance of the mobile app and its features within everyday health management.ResultsThe study revealed a total of 27 design issues (13 for mobile apps and 14 for tablet apps), which were mapped to source events (ie, errors, requests for help, participants' concurrent feedback, and moderator observation). We also applied usability heuristics to identify violations of usability principles. The majority of violations were related to enabling ease of input, screen readability, and glanceability (15 issues), as well as supporting an appropriate match between systems and the real world (7 issues) and consistent mapping of system functions and interactions (4 issues). Feedback from participants also showed the cancer patients’ requirements for support systems and how these needs are influenced by different context-related factors, such as type of access terminal (eg, desktop computer, tablet, mobile phone) and phases of illness. Based on the observed results, we proposed design and functionality recommendations that can be used for the development of mobile apps for cancer patients to support their health management process.ConclusionsUnderstanding and addressing users’ requirements is one of the main prerequisites for developing useful and effective technology-based health interventions. The results of this study outline different user requirements related to the design of the mobile patient support app for cancer patients. The results will be used in the iterative development of the Connect Mobile app and can also inform other developers and researchers in development, integration, and evaluation of mobile health apps and services that support cancer patients in managing their health-related issues.

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.

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.

Mobile apps designed with cultural sensitivity have demonstrated higher user acceptability and greater effectiveness in enhancing self-care skills. However, a significant gap exists in developing such apps for specific populations, such as Portuguese Americans living in southern Massachusetts, home to the second-largest Portuguese community in the United States. This group possesses unique cultural traditions, particularly in dietary practices, including a tendency toward high carbohydrate intake. Tailoring diabetes self-care apps to address these specific cultural requirements could substantially improve diabetes management within this population. The aim of this app development project was to develop a prototype diabetes management app for Portuguese Americans with type 2 diabetes mellitus using the design thinking methodology, incorporating user-centered design principles and cultural sensitivity. This paper describes the phase-2 results, focusing on app design and development. Phase 2 of this app development project adhered to the design thinking methodology delineated by the Hasso Plattner Institute of Design at Stanford University, focusing on 2 critical steps: ideation and prototyping. This phase started in March 2022 and continued until April 2024. The project was driven by a multidisciplinary team consisting of 2 nurse educators; an app development specialist; and 2 graduate research assistants from the university's Computer and Information Sciences Department, both well-versed in mobile app development. Data collected during phase 1, which will be published separately, informed the app design and development process. The prototype of the DiaFriend app (version 1) was designed and developed. The app comprises five features: (1) blood glucose monitoring, (2) weight tracking, (3) carbohydrate tracking, (4) exercise log, and (5) medication reminder. The carbohydrate tracking feature was explicitly tailored to correspond to Portuguese food culture. This paper presents the front-end interface flowchart, demonstrating how the user navigates through each screen. It also discusses the challenges faced during the backend development, such as data not being able to be stored and retrieved. The DiaFriend app (version 1) distinguishes itself from conventional diabetes self-care apps through its emphasis on cultural sensitivity. The development of this app underscores the importance of cultural considerations in health informatics. It establishes a foundation for future research in developing and evaluating culturally sensitive mobile health apps. The adaptation of such technologies has the potential to enhance self-care practices among Portuguese Americans with type 2 diabetes mellitus, with improved glycated hemoglobin levels as a potential outcome. The last step of the design thinking methodology, testing the app, will be conducted in phase 3 and the results will be published elsewhere.

In the current generation of information technology, mobile applications (apps) have become an essential and momentous source to publicize the information across the world. Academia, industries and other organizations have preferred mobile apps rather than classical software. Mobile apps are different from classical software and popularity, adaptability of mobile apps is more with wide range use. The growth of mobile apps across various fields has shown a big challenge for mobile app development industries to deliver apps on time and budget with desired accuracy and performance. Planning of mobile-based projects is a very complex task for the software industry, especially estimation of effort, time and cost for development of mobile apps. There are various literature, method, and model available in the field of classical software but mobile apps are different from classical software by their nature. It has also observed that the selection of input data is also affecting the accuracy of prediction. There is lack of calibrated model and method that administer the immense scope of determination in development of effort estimation for mobile apps. In this paper, various existing techniques of effort estimation have applied on software analytics for mobile apps (SAMOA) dataset for better analysis of suitable estimation technique that fits for mobile App development. The aim of this paper is twofold—(i) to explore the performance of variously established estimation technique on mobile app development (SAMOA dataset). (ii) Analysis of experimental results and, suggesting the best technique for the distinguished mobile app development scenario. The work is carried out adopting four techniques namely multiple linear regressions, Multi-Layer Perceptron Neural Network (MLP-NN), Genetic Algorithm (GA) and Naive forecasting approach. The results have compared with these statistical models. Among all techniques, the experimental results have presented that the GA was outperforming among four effort estimation techniques. Mobile app effort estimation models have built using four-estimation technique using SAMOA dataset. In addition, we investigated and compared various techniques namely MLP, MLP-NN, GA and Naive forecasting approach. Upon construction, accuracy measures MMRE, MRE, PRED(25) represented promising outcomes for mobile apps used in the effort estimation model construction and validation of the process. The analysis presented that GA provided better performance rather than another approach.

Leptospirosis is the most common zoonotic cause of mortality, with most of its burden occurring in tropical regions and low-income countries. It is endemic in Southeast and South Asian nations. Leptospirosis outbreaks occur after natural disasters. In Malaysia, the e-notification system of the Communicable Diseases Control Information System recorded 5217 leptospirosis cases in 2019 with 32 fatalities. The incidence rate was 15.61 per 100,000 people. Male individuals comprised 67% of leptospirosis cases, while people aged 25 to 55 years accounted for 45% of the cases. Information and perception are crucial in influencing positive behavior. Nonetheless, information on urban and rural people's knowledge, attitude, and practice (KAP) regarding the incidence of leptospirosis is limited. We aimed to develop a mobile app with information on leptospirosis and measure its effectiveness in improving KAP regarding leptospirosis among wet market workers in Selangor, Malaysia. A 3-phase study will be conducted and includes development of a mobile app containing information about leptospirosis, analysis of its acceptability, and application of the intervention. Participants will be recruited based on specific inclusion criteria by using purposive sampling. Four wet markets in Hulu Langat district, Selangor, will be selected according to a list provided by local municipal councils. The respondents from each selected wet market will be workers aged 18 years and older. Mobile app development will begin with an idea description, storyboard creation, and content approval through the nominal group technique. The mobile app content will be constructed using the Health Belief Model theory. Subsequently, the usability of the mobile app prototype will be evaluated using the validated Malay version of the System Usability Scale questionnaire for the evaluation of mobile apps. This protocol entails a 12-week intervention stage, in which the baseline assessment is regarded as a pretest evaluation and the follow-up assessment as a posttest evaluation. Participant selection will be based on the inclusion and exclusion criteria. This study will incorporate a set of validated questionnaires created by a group of leptospirosis experts. The validated questionnaire will comprise 9 sections with open-ended questions on sociodemographic data, KAP, and mobile app requirements. Mobile app development and usability testing were completed between January 2024 and March 2025. Participant recruitment is scheduled in April to May 2025 after submission of this manuscript, with the 12-week intervention and data collection running from May to July 2025. As of manuscript submission, recruitment, data collection, and data analysis have not yet begun. Data analysis is expected to be completed by September 2025, and results are anticipated for publication in late 2025. Due to the high number of reported leptospirosis cases in the Hulu Langat district, Selangor, this intervention study will be conducted there. The development of the mobile app may contribute to improving wet market workers' KAP regarding leptospirosis. PRR1-10.2196/75809.

BackgroundThere is a huge number of health-related apps available, and the numbers are growing fast. However, many of them have been developed without any kind of quality control. In an attempt to contribute to the development of high-quality apps and enable existing apps to be assessed, several guides have been developed.ObjectiveThe main aim of this study was to study the interrater reliability of a new guide — the Mobile App Development and Assessment Guide (MAG) — and compare it with one of the most used guides in the field, the Mobile App Rating Scale (MARS). Moreover, we also focused on whether the interrater reliability of the measures is consistent across multiple types of apps and stakeholders.MethodsIn order to study the interrater reliability of the MAG and MARS, we evaluated the 4 most downloaded health apps for chronic health conditions in the medical category of IOS and Android devices (ie, App Store and Google Play). A group of 8 reviewers, representative of individuals that would be most knowledgeable and interested in the use and development of health-related apps and including different types of stakeholders such as clinical researchers, engineers, health care professionals, and end users as potential patients, independently evaluated the quality of the apps using the MAG and MARS. We calculated the Krippendorff alpha for every category in the 2 guides, for each type of reviewer and every app, separately and combined, to study the interrater reliability.ResultsOnly a few categories of the MAG and MARS demonstrated a high interrater reliability. Although the MAG was found to be superior, there was considerable variation in the scores between the different types of reviewers. The categories with the highest interrater reliability in MAG were “Security” (α=0.78) and “Privacy” (α=0.73). In addition, 2 other categories, “Usability” and “Safety,” were very close to compliance (health care professionals: α=0.62 and 0.61, respectively). The total interrater reliability of the MAG (ie, for all categories) was 0.45, whereas the total interrater reliability of the MARS was 0.29.ConclusionsThis study shows that some categories of MAG have significant interrater reliability. Importantly, the data show that the MAG scores are better than the ones provided by the MARS, which is the most commonly used guide in the area. However, there is great variability in the responses, which seems to be associated with subjective interpretation by the reviewers.

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.