Mobile Healthcare Applications Research Articles

Social Support, eHealth Literacy, and mHealth Use in Older Adults With Diabetes: Moderated Mediating Effect of the Perceived Importance of App Design.

Mobile healthcare has emerged as a prominent technological solution for self-management of health. However, the development and utilization of tailored mobile healthcare applications for older adults with diabetes mellitus remain limited. This study examined the relationship between social support and mobile healthcare use and further explored how this relationship varies with eHealth literacy and application design among older adults with diabetes mellitus. A descriptive cross-sectional trial was conducted with a structured self-report questionnaire, surveying 252 South Korean older adults with diabetes mellitus via offline and online modes. The mediating effect and moderated mediating effect were analyzed with the PROCESS macro of SPSS. eHealth literacy mediated the relationship between social support and mobile healthcare use. High levels of eHealth literacy and social support may increase mobile healthcare use among older adults with diabetes. Application design aesthetics facilitated mobile healthcare use. Future researchers, healthcare providers, and developers can contribute to the development of tailored mobile healthcare applications for older adults with diabetes mellitus by considering application design aspects such as font size, color, and menu configuration.

MedConnect PLUS: Health Management System

Abstract: The utilization of mobile applications in healthcare represents a frontier of innovation with the potential, to significantly enhance patients' daily healthcare management. These applications have the capacity to improve the efficiency of healthcare delivery, ultimately leading to cost reduction, and play a pivotal role in disease prevention by influencing behavior change. The paper introduces a model for an interactive healthcare application designed to meet the collaborative needs of both doctors and patients. The envisioned mobile application seeks to optimize communication among various stakeholders in the healthcare sector, including doctors, pharmacists and patients, thereby enhancing overall healthcare service and delivery. Object Oriented Analysis is employed in the software development process. This proposed mobile application is geared towards facilitating effective communication by incorporating advanced technologies to streamline processes such as appointment scheduling, health record management, and patient-doctor interactions. Emphasis is placed on the application's commitment to data security and compliance with healthcare regulations, ensuring the protection of sensitive patient information within a secure environment. The user-friendly interfaces tailored for both patients and doctors highlight the application's intention to cultivate a more interconnected and accessible healthcare ecosystem.

Cloud Computing Assisted Mobile Healthcare Systems Using Distributed Data Analytic Model

Distributed cloud technologies enable mobile healthcare applications to support end users constantly. Data from electronic health records is made available through combination of user needs and heuristic mining. Because of inefficient data storage and reorganization, service and recommendation failures occur prematurely. A Distributed Data Analytics and Organization Model (DDAOM) is established in this article as a solution to the inefficiency of managing large amounts of data. Using this method, errors caused by performing several computations or storing large amounts of data in the medical field are minimized. Data organization and mining under predetermined schedules or factors provide information relevant to user services. One-to-many computations with varying input and output data allocations (for services) are executed in federated learning. The local input from several edges may be handled by allocating storage in a decentralized manner. The federated learning system uses the memory of past states to direct the allocation. Differentiating the states is necessary to allocate services and prevent mining in certain areas. With the help of realistic learning iterations, state management is maintained, guaranteeing the smooth deployment of services. Delays in storage and mining, uneven service provisioning, and service backlogs are used to evaluate the effectiveness of the suggested model.

Development of Legal Regulation of the Use of Mobile Medical Technologies (mHealth) in the Law of International Integration Associations: European Union Experience

The paper examines the experience of legal regulation of the use of mobile medical technologies (MMT, mHealth) in the largest regional integration association — the European Union (EU). It is noted that digital healthcare is a multifaceted concept that includes various aspects of public health and the digital environment surrounding it. Digitalization of healthcare covers medical processes, including software to support the work of doctors (including telemedicine technologies), tools for managing a medical institution, remote interaction with patients and monitoring such interaction; big data analytics for drug development, clinical research management, patient population studies; additional patient-oriented tools and including applications related to the determination of physical condition and the course of treatment, as well as compliance with the medication regimen. The paper provides a detailed overview of the main EU documents in the relevant field, illustrates the impact of judicial practice on the development of regulation in the field of mobile medical technologies, and analyzes the mechanisms of selfregulation in this area using the example of specific court cases. It is emphasized that while self-regulation on the part of the applications store can set developers of mobile healthcare applications in the right direction by converting the provisions of Regulation 2016/679 (GDPR) into technical requirements for preliminary approval, compliance with privacy provisions is facilitated by increased awareness of both application users and developers, as well as brokers of medical data about the risks to the observance of fundamental human rights. from the side of mobile healthcare applications. In conclusion, the authors formulated the key problems and ways to improve EU regulatory framework in the field of mobile medical technologies, recommended the use of EU best practices in the development of MMT regulatory regulation in the Russian Federation and integration associations with its participation.

Long-Term Efficacy of primary care combining a mobile healthcare application with human coaching

Abstract Background Chronic diseases have become a global burden, and digital self-healthcare using mobile devices has gained importance in managing these conditions. However, barriers to implementing mobile self-management healthcare applications in current primary care system, and previous research has focused on short-term effects. This study aims to evaluate the long-lasting effect of combining human coaching with mobile self-management healthcare applications for chronic disease patients in primary healthcare services. Methods The study recruited 178 patients with chronic diseases from participating primary care clinics. The intervention group (N = 128) received a 12-week mobile self-management healthcare application service combined with traditional primary care, while the control group (N = 50) received only traditional healthcare. The Noom application was used, with two weekly human coaching sessions by a nutritionist. A telephone survey on weight changes was conducted one year after the intervention. Results The intervention group showed a greater weight loss compared to the control group during the intervention period (Intervention: -1.29 ± 2.94 vs Control: -0.38 ± 1.72, P-value 0.002). Although there was no statistically significant difference in additional weight change between the two groups during the follow-up period, the difference in weight loss during the intervention period was maintained (Intervention: -2.16 ± 5.54 vs Control: -1.06 ± 3.24, P-value: 0.008). Additionally, among the intervention group continuously for 1 year using the health management application, the average weight loss was higher than the other groups. Conclusions Combining a mobile self-management healthcare application with human coaching has long-lasting effects and can be effective in primary healthcare services. This suggests that such an approach has the potential to be a treatment option in current primary healthcare systems, but further large-scale long-term studies are needed. Key messages • This study suggests that using mobile self-management healthcare apps with human coaching can be an effective long-term treatment option for chronic disease patients in primary healthcare services. • The combination of the two methods may provide better outcomes than traditional healthcare services alone.

A configurable hardware-efficient ECG classification inference engine based on CNN for mobile healthcare applications

—Electrocardiogram (ECG) processors for healthcare have been widely used, however most of them can only adapt to specific applications, lacking flexibility. For achieving scalable on-chip ECG classification, a flexible inference engine based on one-dimensional (1-D) convolutional neural network (CNN) is proposed. By utilizing the proposed computing strategy based on systolic arrays, filter level parallelism and output channel parallelism are achieved. The configurable processing units (PUs) and modifiable instruction registers allow this inference engine to support computing of 1-D convolutional layers or fully connected layers with different scales. Based on the proposed data buffers system with multi-level storage structure, the input feature values and weight values are reused, thereby reducing hardware overhead and memory access power. This design has been validated on FPGA using our proposed two arrhythmia classification models that represent low energy consumption and high accuracy requirements, achieving accuracy of 98.9% and 99.3%, respectively, with energy consumption of 2.05 μJ and 14.27 μJ per classification at 200 MHz. The hardware implementation results indicate that good configurability enables our design to adapt to different ECG classification scenarios, effectively improving the hardware universality in mobile healthcare applications.

Trends in Development of Applied Social and Communication Technol-Ogies in Medical Field: Mobile Applications and Programmes in Healthcare

The purpose of the article is to conduct a comprehensive analysis of the trends in the development of applied social and communication technologies in the medical sector, in particular, to trace dynamics of growth in the number of mobile applications and programmes in healthcare sector. The research methodology is formed by general scientific and special methods of studying the problem, the use of which allowed the authors to achieve the goal. The combination of the methods used helped to clarify the logical sequence and trends in the development of applied social and communication technologies in the modern information space of society. The basic principle was the principle of historicism, which implies consideration of any phenomenon in its self-development under the influence of various factors. The historical and systemic method is aimed to analyse society as a whole and the transformations within it caused by changes in the information and communication space. Quantitative methods are used to process the results of analytical research and to diagnose the phenomena under study. The scientific novelty of the work is to expand the understanding of the trends in the development of applied social and communication technologies in the medical field. The authors' study analysed modern domestic medical information systems, the possibilities of their interaction with eHealth, and identified priority technological areas in the medical sector, such as virtual reality, 3D printing, robotics, artificial intelligence, augmented reality, a global network of medical facilities, wearable devices, smart technologies, and precision (personalised) medicine. The authors state that in recent years, attention has increased to applications, mobile sensors and digital media in order to get help in maintaining one's health. Conclusions. The study has proved the positive dynamics in the growth of mobile applications and programmes in healthcare sector and determined the trends of the further development of information technologies in the medical sector.
 Key words: healthcare system, information technologies, medical information systems, mobile applications in healthcare.

Neural network models selection scheme for health mobile app development

Mobile healthcare application (mHealth app) assists the frontline health worker in providing necessary health services to the patient. Unfortunately, existing mHealth apps continue to have accuracy issues and limited number of disease detection systems. Thus, an intelligent disease diagnostics system may help medical staff as well as people in poor communities in rural areas. This study proposes a scheme for simultaneously selecting the best neural network models for intelligent disease detection systems on mobile devices. To find the best models for a given dataset, the proposed scheme employs neural network models capable of evolving altered neural network architectures. Eight neural network models are developed simultaneously and then implemented on the Android Studio platform. Mobile health applications use pre-trained neural network models to provide users with disease prediction results. The performance of the mobile application is measured against the existing available datasets. The trained neural network engines perform admirably, detecting 7 out of 8 diseases with high accuracy ranging from 86.00% to 100% and a low detection accuracy of 63%. The detection times vary from 0.01 to 0.057 seconds. The developed mHealth app may be used by health workers and patients to improve resource-poor community health services and patients' healthcare quality.

COMPASS App: A Patient-centered Physiological based Pain Assessment System

Chronic pain patients lack at-home pain assessment and management tools. The existing chronic-pain mobile applications are either solely relying on self-report pain levels or restricted to formal clinical settings. Our app, abbreviated from an NSF-funded project entitled Novel Computational Methods for Continuous Objective Multimodal Pain Assessment Sensing System (COMPASS), is a multi-dimensional pain app that collects physiological signals to predict objective pain levels and trace daily at-home activities by incorporating a daily check-in section. We conducted a usability test with 33 healthy participants under pain conditions. The results provided initial support for the validity of the signals in predicting internalizing pain levels among the participants. With further development and testing, we believe the COMPASS app system has the potential to be used by both patients and clinicians as an additional tool to better assess and manage pain, especially for mobile healthcare applications.

보건소 모바일 헬스케어 어플리케이션 서비스 경험 분석 및 서비스 개선에 관한 연구

보건소 모바일 헬스케어 어플리케이션 서비스 경험 분석 및 서비스 개선에 관한 연구

Operationalising AI ethics through the agile software development lifecycle: a case study of AI-enabled mobile health applications

AbstractAlthough numerous ethical principles and guidelines have been proposed to guide the development of artificial intelligence (AI) systems, it has proven difficult to translate these principles into actionable practices beyond mere adherence to ethical ideas. This is particularly challenging in the context of AI systems for healthcare, which requires balancing the potential benefits of the solution against the risks to patients and the wider community, including minorities and underserved populations. To address this challenge, we propose a shift from one-size-fits-all ethical principles to contextualized case-based ethical frameworks. This study uses an AI-enabled mHealth application as a case study. Our framework is built on existing ethical guidelines and principles, including the AI4People framework, the EU High-Level Expert Group on trustworthy AI, and wider human rights considerations. Additionally, we incorporate relational perspectives to address human value concerns and moral tensions between individual rights and public health. Our approach is based on ”ethics by design,” where ethical principles are integrated throughout the entire AI development pipeline, ensuring that ethical considerations are not an afterthought but implemented from the beginning. For our case study, we identified 7 ethical principles: fairness, agility, precision, safeguarding humanity, respect for others, trust and accountability, and robustness and reproducibility. We believe that the best way to mitigate and address ethical consequences is by implementing ethical principles in the software development processes that developers commonly use. Finally, we provide examples of how our case-based framework can be applied in practice, using examples of AI-driven mobile applications in healthcare.

Patient-targeted mobile applications in healthcare.

There has been an increase in the number of healthcare-related applications targeted at patients for use on mobile phones. With an increasing proportion of the population using such applications, it is important to understand the associated limitations, safety concerns and challenges of legalisation. This article explores the impact of these applications on frontline care and patient wellbeing, evaluating the literature surrounding the benefits and challenges of patient-targeted mobile applications in health care and analysing the limitations of existing research. The proclaimed benefits of such applications are not always evidence based. Furthermore, many healthcare applications are created by laypeople and not validated by healthcare authorities, creating a potential to cause patient harm. Further research is needed to identify long-term effects on both healthcare systems and individuals' psychosocial wellbeing. However, research in this field often lacks a universal perspective and may be influenced by underlying financial motives to promote use of the applications.

Understanding the mobile healthcare applications continuance: The regulatory focus perspective

BackgroundAlthough mobile healthcare (mHealth) applications have proliferated and offer new opportunities for personal health management, many users exhibit discontinuance behavior. Various factors in mHealth applications can strongly impact users’ continuance behavior, but it is not yet fully understood how they interact with each other to yield maximized effects. This study highlights the importance of identifying the antecedents and moderators of continuance intention to broaden the demographic reach of mHealth applications and thus contribute to maintaining a sustainable healthcare system. ObjectiveThis research explores three dimensions of perceived values (hedonic, utilitarian, and social) in mHealth platforms that lead to user satisfaction and, ultimately, continuance intention. It further investigates the moderating effects of personal traits defined by regulatory focus on the relationship between perceived value and user satisfaction. MethodsData was collected from 259 respondents with experience using the Samsung Health application. The research tests the proposed model and hypotheses by implementing PLS-SEM and multi-group analyses. ResultsEach dimension of perceived values positively influences user satisfaction, with hedonic and utilitarian values exhibiting stronger relationships. Regarding moderating effects, promotion (versus prevention) focus has a stronger enhancing effect on the positive relationship between utilitarian value and user satisfaction. In contrast, prevention (versus promotion) focus more strongly enhances the positive relationship between hedonic value and user satisfaction. Regulatory focus does not yield a significant moderating effect on the relationship between social value and user satisfaction. User satisfaction exerts a strong positive influence on continuance intention in mHealth environments. ConclusionsThe moderating effect of individuals’ regulatory focus has been identified. Combined effects of antecedents and moderators on user satisfaction influence their continuance intention in mHealth ecologies. Considering individual users’ characteristics may guide mHealth application developers to design personalized platforms and establish enforced marketing strategies.

#4102 THE IMPACT OF MOBILE HEALTH ON HOME BLOOD PRESSURE AND HEALTH LITERACY IN CHRONIC KIDNEY DISEASE

Abstract Background and Aims Mobile health (mHealth) management is an emerging therapeutic strategy for chronic diseases. mHealth has been considered to improve self-care management and assist in detecting a worsening health status early. However, the effect of mHealth management on the blood pressure (BP) of patients with chronic kidney disease (CKD) has not been well-studied. This study aimed to access the association between mHealth management and BP control in CKD. We also investigated the association between mHealth and health literacy(HL) in CKD. Method Kaohsiung Medical University Hospital designed and developed a new healthcare mobile application called iCKD. The application has several major features, including BP monitoring, alarms, and a warning system. We randomly assigned 122 CKD patients stages 1-5 to utilize iCKD or paper records (control group) for BP management. The primary outcome was the portion of reaching the target goal, defined as office BP less than 130/80 mmHg, during the 6-month study. Trained nurses interviewed CKD patients using structured questionnaires to evaluate HL. Results Baseline kidney function and BP were not significantly different between iCKD and control groups. During the study period, 11 participants had withdrawal.42.3% of the iCKD group (22/52) had the BP control reaching the target goal, while only 22.4% (11/49) in the control group(p = 0.03). Regarding HL, CKD patients with BP reaching the target goal had higher total scores than those without. The score for iCKD group, ranging from 29.29 to 32.85, were higher than the control group, ranging from 28.94 to 31.03. (p = 0.01). Conclusion The iCKD group had a higher proportion of reaching the BP target goal and better HL score than the control group. This study demonstrates that mHealth can improve the CKD population's health literacy and BP management.

Exploring factors influencing the adoption of mobile healthcare technologies: perspectives from designers, consultants and users’ preferences

PurposeToday, the use of smart technologies in healthcare systems is experiencing exponential growth, and the future of healthcare is seemingly closely intertwined with such technologies. Thus, any exploration of the factors that influence human health and healthcare systems inevitably touches upon the subject of new technologies. This study aims to design a conceptual model to investigate the elements that affect individuals' openness to accepting and using mobile healthcare applications (mHealth apps) and their reciprocal effects.Design/methodology/approachAfter a brief review of the literature, the authors identify the influential factors in the acceptance of smart technologies in healthcare systems and present a conceptual model in this regard. Next, the authors analyze the factors and variables and the extent of their impact by a structural equation modeling (SEM) approach. The statistical population of this study consists of 421 individuals including the developers, consultants and users (i.e. patients) of mHealth apps. Data analysis was done on the statistical software SPSS v.26, while SEM was carried out using the partial least squares (PLS) method on the modeling software SmartPLS.FindingsThe results indicate that user, consultant and developer preferences have a positive and significant impact on time, quality of life, managing chronic conditions and cooperation, and these constructs (system performance) finally have a positive and significant impact on the acceptance of mobile healthcare technologies.Originality/valueThis paper shows that mHealth apps can have a remarkable role in the prevention and treatment of medical conditions, and it is strongly recommended that this technology be utilized in the studied region.

Software-driven secure framework for mobile healthcare applications in IoMT

The traditional healthcare systems require more data storage and not a quick responsive mode. The new era of intelligent healthcare systems uses advanced frameworks and devices to work with Internet of things (IoT), Cloud Computing, edge computing devices, and the Internet of Medical Things (IoMT). These technology adoptions may drastically increase healthcare systems performance and are available anytime and anywhere to replace traditional medical methods – the organizations in the network exchange the patient data that has been gathered. The healthcare systems are therefore susceptible to a variety of threats. The attacker may exploit many attacks during the transmission. This paper introduces a novel mechanism of A Secure Robust Privacy-Preserving Authentication and Key Agreement Framework for Mobile Healthcare Applications. The proposed framework collects the patient’s data using wearable devices called sensors, and the collected data is shared with various entities using a secure mechanism. The proposed framework uses Elliptic Curve Cryptography (ECC). Digital sign is created and validated through the Elliptic Curve Digital Signature Algorithm (ECDSA). Security properties of the proposed framework are analyzed through standard model checking tool Automated Validation of Internet Security Protocols (AVISPA). The suggested protocol is simple to develop and can withstand network-related threats.

Usability of a mobile application for the clinical follow-up of patients with chronic obstructive pulmonary disease and home oxygen therapy

BackgroundTechnological health tools (e-Health) may potentially facilitate the treatment of patients with chronic diseases through development of self-management and -care skills in patients and caregivers. However, these tools are usually marketed without prior analysis and without providing any context to final users, which frequently results in low adherence to their use. PurposeTo determine the usability of and satisfaction toward a mobile app for the clinical monitoring of patients with chronic obstructive pulmonary disease (COPD) receiving oxygen therapy at home. MethodsThis was a participative-qualitative study focused on final users—with direct intervention by patients and professionals—consisting of three phases as follows: (i) medium-fidelity mockups design, (ii) development of a usability test for each user profile, and (iii) assessment of the satisfaction level regarding the usability of the mobile app. A sample was established and selected through non-probability convenience sampling and was divided into two groups as follows: healthcare professionals (n = 13) and patients (n = 7). Each participant received a smartphone with mockup designs. The “think-aloud” method was applied in the usability test. Participants were audio recorded and the anonymous transcriptions were analyzed, highlighting fragments about mockups characteristics and the usability test. The difficulty level of the tasks was assessed with a scale from 1 (very easy) to 5 (too difficult), and task non-completion was considered a critical mistake. The satisfaction level related to test usability was assessed with a 4-score Likert scale ranging from 4 (totally agree) to 1 (totally disagree). ResultsRegarding the difficulty level, >60% of professionals described most tasks as “very easy” and 70% of patients as “easy.” No participant made critical mistakes and both groups reported a high satisfaction level regarding the usability variables. The patient and professionals group required 18 and 11 min to complete all tasks, respectively. ConclusionsParticipants described the app as intuitive and easy to use. The usability satisfaction results show a high level of satisfaction for both groups. This positive assessment and performance in user tests showed that the mobile application was able to be apprehended and used by participants in the circumstances of use in the usability tests. Usability evaluation through satisfaction surveys and qualitative data analysis allows for greater insight into the use of mobile applications in healthcare.

Usability of a mobile application for health professionals in home care services: a user-centered approach

The use of mobile devices by healthcare professionals has led to rapid growth in the development of mobile healthcare applications designed to improve healthcare services. This study was conducted to assess the acceptability and usability of a mobile application for health professionals in relation to their work in hospitalization at home. A mixed methods approach was used. Acceptance, included the satisfaction of the professionals, attitudes toward using the application, and intention or willingness to continue using the application. Usability tests were performed in laboratory analyzing five controlled clinical tasks, and the interaction of the participants with the mobile application was based on the six basic facial expressions published by the American Psychological Association. Perceived satisfaction was assessed using the computer system usability questionnaire. Thirty-two participants completed the task scenarios and questionnaire. More than 90 per cent of participants were able to complete the tasks with only some difficult with vital signs. Satisfaction had a score of 6.18/7 (SD: 0.76), and recommendation of the mobile application had a score of 6.21/7 (SD: 0.81). This study showed a significant usability and acceptability of this mobile application, in terms of effectiveness, efficiency, and satisfaction.

Healthcare Mobile Application

Healthcare Mobile Application

Factors Influencing the Aged in the Use of Mobile Healthcare Applications: An Empirical Study in China.

Mobile healthcare applications are of significant potential value in the development of the aged-care industry due to their great convenience, high efficiency, and low cost. Since the cognition and utilization rates of mobile healthcare applications for the elderly are still low, this study explored the factors that affect the elderly's adoption of mobile healthcare applications. This study conducted a questionnaire survey on the elderly in China and received 365 valuable responses. This study combined the technology acceptance model, protection motivation theory, and perceived risk theory to build a research model of factors affecting the use of mobile healthcare applications by the elderly. The data were analyzed using a structural equation model. The results were as follows: according to the empirical research, (1) perceived usefulness and perceived ease of use positively affect the use attitude of the elderly; perceived usefulness and user attitude positively affect the behavior intention of the elderly; perceived ease of use positively affects perceived usefulness; (2) perceived severity has a significant positive correlation with use attitude; perceived susceptibility and attitude to use have no significant impact; (3) perceived risk is negatively correlated with the use attitude and behavioral intention. The above-mentioned factors should be taken into consideration during the development of mobile healthcare applications for the aged to upgrade the overall service quality of mobile healthcare applications, thus enhancing the operational level of mobile healthcare applications and the health literacy of the aged.