AI-Based mHealth App for Covid-19 or Cardiac Diseases Diagnosis and Prognosis

Covid-19 has rapidly spread and affected millions of people worldwide. For that reason, the public healthcare system was overwhelmed and underprepared to deal with this pandemic. Covid-19 also interfered with the delivery of standard medical care, causing patients with chronic diseases to receive subpar care. As chronic heart failure becomes more common, new management strategies need to be developed. Mobile health technology can be utilized to monitor patients with chronic conditions, such as chronic heart failure, and detect early signs of Covid-19, for diagnosis and prognosis. Recent breakthroughs in Artificial Intelligence and Machine Learning, have increased the capacity of data analytics, which may now be utilized to remotely conduct a variety of tasks that previously required the physical presence of a medical professional. In this work, we analyze the literature in this domain and propose an AI-based mHealth application, designed to collect clinical data and provide diagnosis and prognosis of diseases such as Covid-19 or chronic cardiac diseases. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Development of mHealth-Apps for Hearing Aids – Requirements and Assessments of a First Prototype

An aging of the working population is expected. Consequently, age-related impairments of sensory functions (e.g., hearing impairment) will become more prominent. An increase of people with hearing impairment can already be observed today. In the last years, the importance of digitalization has increased constantly. This was further driven by the COVID19-pandemic. Therefore, the question whether mHealth-apps could be able to improve the first start experience of possible new hearing aid users and how such an app should be designed has continuously become more important. Former research showed that participants rated possible hearing app-functions significantly different. The aim of the presented study was to verify these results and to extend it with additional functions. Furthermore, possible future users should assess first paper-based prototypes. Therefore, an exploratory online study was conducted. Overall, the sample consists of 41 participants (29 female;19–58 years old). 18 of them were subjectively at least mild hearing impaired. The results of the study show that participants rated possible functions and the different hearing app-prototypes significantly different. Interestingly, effects of hearing impairment and gender can be shown. Overall, the results can improve the development of a new mHealth-app to support new users of hearing aids. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Understanding the Antecedents and Effects of mHealth App Use in Pandemics: A Sequential Mixed-Method Investigation.

Pandemics such as COVID-19 pose serious threats to public health and disrupt the established systems for obtaining healthcare services. Mobile health (mHealth) apps serve the general public as a potential method for coping with these exogenous challenges. However, prior research has rarely discussed the antecedents and effects of mHealth apps and their use as a coping method during pandemics. Based on the technology acceptance model, empowerment theory, and event theory, we developed a research model to examine the antecedents (technology characteristics and event strength) and effects (psychological empowerment) of mHealth apps and their use. We tested this research model through a sequential mixed-method investigation. First, a quantitative study based on 402 Chinese mHealth users who used the apps during the COVID-19 pandemic was conducted to validate the theoretical model. A follow-up qualitative study of 191 online articles and reviews on mHealth during the COVID-19 pandemic was conducted to cross-validate the results and explain the unsupported findings of the quantitative study. The results show that (1) the mHealth app characteristics (perceived usefulness and perceived ease of use) positively affect mHealth app use; (2) mHealth app use positively affects the psychological empowerment of mHealth users; and (3) the characteristics of pandemic events (event criticality and event disruption) have positive moderating effects on the relationship between mHealth app characteristics and mHealth app use. This study explains the role of mHealth apps in the COVID-19 pandemic on the micro-level, which has implications for the ways in which mHealth apps are used in response to public pandemics.

A "No-Code" App Design Platform for Mobile Health Research: Development and Usability Study.

BACKGROUND: A challenge facing researchers conducting mobile health (mHealth) research is the amount of resources required to develop mobile apps. This can be a barrier to generating relevant knowledge in a timely manner. The recent rise of "no-code" software development platforms may overcome this challenge and enable researchers to decrease the cost and time required to develop mHealth research apps. OBJECTIVE: We aimed to describe the development process and the lessons learned to build Pathverse, a no-code mHealth app design platform. METHODS: The study took place between November 2019 and December 2021. We used a participatory research framework to develop the mHealth app design platform. In phase 1, we worked with researchers to gather key platform feature requirements and conducted an exploratory literature search to determine needs related to this platform. In phase 2, we used an agile software framework (Scrum) to develop the platform. Each development sprint cycle was 4 weeks in length. We created a minimum viable product at the end of 7 sprint cycles. In phase 3, we used a convenience sample of adults (n=5) to gather user feedback through usability and acceptability testing. In phase 4, we further developed the platform based on user feedback, following the V-model software development process. RESULTS: Our team consulted end users (ie, researchers) and utilized behavior change technique taxonomy and behavior change models (ie, the multi-process action control framework) to guide the development of features. The first version of the Pathverse platform included features that allowed researchers to (1) design customized multimedia app content (eg, interactive lessons), (2) set content delivery logic (eg, only show new lessons when completing the previous lesson), (3) implement customized participant surveys, (4) provide self-monitoring tools, (5) set personalized goals, and (6) customize app notifications. Usability and acceptability testing revealed that researchers found the platform easy to navigate and that the features were intuitive to use. Potential improvements include the ability to deliver adaptive interventions and add features such as community group chat. CONCLUSIONS: To our knowledge, Pathverse is the first no-code mHealth app design platform for developing mHealth interventions for behavior. We successfully used behavior change models and the behavior change technique taxonomy to inform the feature requirements of Pathverse. Overall, the use of a participatory framework, combined with the agile and hybrid-agile software development process, enabled our team to successfully develop the Pathverse platform.

Quality Assessment of Digital Health Applications: Protocol for a Scoping Review.

BACKGROUND: All over the world, development and usage of mobile health (mHealth) apps is increasing. While apps offer numerous opportunities to improve health care, there are associated problems that differ significantly from those of traditional health care services. Further investigations on the quality of mHealth apps are needed to address these problems. OBJECTIVE: This study aims to identify and map research on quality assessment and quality assurance of mHealth apps and their transferability to continuous quality assurance of mHealth apps. METHODS: The scoping review will follow published methodological frameworks for scoping studies as well as Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews criteria. Electronic databases (Medline, EMBASE, and PsycINFO), reference lists of relevant articles, and websites of relevant institutions will be searched. Two reviewers will independently assess eligibility of articles. Therefore, a 2-stage (title and abstract, followed by full text) screening process was conducted. Quality management systems and quality assessment tools will be analyzed and included in our review. Particular focus is placed on quality dimensions. RESULTS: This scoping review provides an overview of the available evidence and identifies research gaps regarding continuous quality assessment of mHealth apps. Thereby, relevant quality dimensions and criteria can be identified and their eligibility and relevance for the development of a continuous quality assurance system of mHealth apps can be determined. Our results are planned to be submitted to an indexed, peer-reviewed journal in the second half of 2022. CONCLUSIONS: This is the first review in the context of continuous quality assurance of mHealth apps. Our results will be used within the research "Continuous quality assurance of Digital Health Applications" ("QuaSiApps") project funded by the German Federal Joint Committee. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/36974.

PUBLIC AWARENESS, USES, AND ACCEPTANCE TOWARDS GOVERNMENT HEALTH MOBILE APPS DURING THE COVID-19 LOCKDOWN: THE CASE OF SAUDI ARABIA

This study aimed to investigate the public awareness, use, and acceptability of the Sehha, Mawid, and Tetamman mobile health applications during the COVID-19 pandemic in Saudi Arabia. A cross-sectional online study was conducted using a conve-nience sample of 554 participants from the Riyadh and Makkah regions during the lock-down in May 2020. One-third of the respondents were aware of all three apps (31.1%). Participants used the mobile health apps most frequently to obtain information about COVID-19, book appointments and audio-video consultations, and as a COVID-19 symp-toms checker. However, their use for self-isolation app for location monitoring or to check COVID-19 lab results were insufficient as intended. A comparison of the number of downloads to actual users showed that the user rates were 42.6%, 87.2%, and 91.54% for the Tetamman, Sehha, and Mawid apps, respectively. The overall acceptance rates for the Mawid and Tetamman apps were 4.21±0.62 vs. 4.22±0.58, while the Sehha app reported a moderate mean score 3.73±1.20. The lowest subscale was related to the reliability 2.18±2.09, 2.38±2.16 and 4.40±0.65 for Mawid, Sehha and Tetamman, respec-tively, while the learnability scale ranged from 4.04±1.28, 4.44±0.54, and 4.52±0.67 in the Sehha, Tetamman and Mawid, respectively. Despite the low usage of some mHealth functions, we identify a positive attitude towards the mHealth apps’ acceptability. Hence, it is possible to improve their usage by increasing the public’s trust in these apps in Saudi Arabia. © 2022 ICIC International.

Modeling the Prediction of Continued Usage of COVID-19 mhealth App in India

Indian m-health app Aarogya Setu has made a significant contribution in terms of contactability tracing and disease management during the initial days of the COVID-19 pandemic, with its contact tracking approach to infectious individuals and its health tips for eliminating new coronaviruses. The goal of this study is to forecast whether or not Indian consumers will continue to use this app. According to previous studies, the context or setting has a substantial impact on the customer's perceived value. The current study's unique setting is to investigate the parameters impacting Indians' ongoing use of the mobile mHealth app AarogyaSetu. An extended technology adoption model (TAM) has been proposed and tested to achieve this wide goal, with the addition of three additional constructs: social influence, health consciousness, and trust in the app developer. © 2021 IEEE.

The Association between mHealth App Use and Healthcare Satisfaction among Clients at Outpatient Clinics: A Cross-Sectional Study in Inner Mongolia, China.

Mobile health (mHealth) applications (apps) have been developed in hospital settings to allocate and manage medical care services, which is one of the national strategies to improve health care in China. Little is known about the comprehensive effects of hospital-based mHealth app use on client satisfaction. The aim of this study was to determine the relationship between the full range of mHealth app use and satisfaction domains among clients attending outpatient clinics. A cross-sectional survey was conducted from January to February 2021 in twelve tertiary hospitals in Inner Mongolia. After the construction of the mHealth app use, structural equation modeling was used for data analysis. Of 1889 participants, the standardized coefficients ß on environment/convenience, health information, and medical service fees were 0.11 (p < 0.001), 0.06 (p = 0.039), and 0.08 (p = 0.004), respectively. However, app use was not significantly associated with satisfaction of doctor-patient communication (ß = 0.05, p = 0.069), short-term outcomes (ß = 0.05, p = 0.054), and general satisfaction (ß = 0.02, p = 0.429). Clients of the study hospitals were satisfied with the services, but their satisfaction was not much associated with mHealth use. The limitation of the mHealth system should be improved to enhance communication and engagement among clients, doctors, and healthcare givers, as well as to pay more attention to health outcomes and satisfaction of clients.

The usefulness of the nutrition apps in self-control of diabetes mellitus - the review of literature and own experience.

Intensive technology development as well as the COVID-19 pandemic has contributed to the increased interest in the telemedicine and mHealth sector. Increasing availability and use of mobile devices as well as the constantly growing number of nutritional mobile applications, resulted in creating new tools for food and meals nutrients calculation which can be used by patients with diabetes. Variety of mobile applications and multiple functions included in them enable finding applications focused on individual patients' needs. The scientific data coming from research conducted so far suggest that the regular use of mobile nutritional applications contributes to improving metabolic control of diabetes and the reduction of the value of glycated hemoglobin in patients with diabetes. Innovative solutions bring hope also for a significant improvement in the quality of life of patients. The aim of this article was to summarize the EBM knowledge about the use of mHealth in self-control and diet of patients with diabetes, especially type 1 and to present and assess the nutrition mobile applications available in polish language according to their functionality in diabetic self-control.

Adoption of Health Mobile Apps during the COVID-19 Lockdown: A Health Belief Model Approach.

This study aimed to investigate the adoption of the Sehha, Mawid, and Tetamman mobile health applications during the COVID-19 pandemic in Saudi Arabia. The present study investigated factors influencing app use intention based on the Health Belief Model (HBM) approach. This study was conducted using a sample of 176 participants from the Riyadh and Makkah regions during the lockdown in May 2020. This study uses structural equation modeling for data collected using SmartPLS 3.3.9 (GmbH, Oststeinbek, Germany) to examine the effect of constructs on the model. The most important predictor was the perceived benefits of the mobile health apps, followed by self-efficacy. The perceived barriers and cues to action have no significant effect on behavioral intention. The perceived benefits and self-efficacy as keys can provide an overview to the government and to health organizations for taking into account the most important factors of the adoption of mobile health apps, meaning that the developer must adjust to the characteristics of the community of people that need applications that provide many benefits and have an impact.

Protocol of a Single-Blind Two-Arm (Waitlist Control) Parallel-Group Randomised Controlled Pilot Feasibility Study for mHealth App among Incontinent Pregnant Women.

BACKGROUND: The delivery of pelvic floor muscle training (PFMT) through mHealth apps has been shown to produce promising results in improving pelvic floor muscle strength and urinary incontinence (UI). However, there is limited evidence on mHealth apps designed for pregnant women who are at high risk of developing UI. This pilot study aims to evaluate the feasibility of conducting an effectiveness trial for a newly developed PFMT app among pregnant women in Malaysia. METHODS: This is a prospective, single-centre, single-blind, randomised controlled pilot feasibility study: The Kegel Exercise Pregnancy Training app (KEPT-app) Trial. Sixty-four incontinent pregnant women who attended one primary care clinic for the antenatal follow-up will be recruited and randomly assigned to either intervention or waitlist control group. The intervention group will receive the intervention, the KEPT-app developed from the Capability, Opportunity, Motivation-Behaviour (COM-B) theory with Persuasive Technology and Technology Acceptance Model. DISCUSSION: This study will provide a fine-tuning for our future randomised control study on the recruitment feasibility methods, acceptability, feasibility, and usability of the KEPT-app, and the methods to reduce the retention rates among pregnant women with UI. TRIAL REGISTRATION: This study was registered on ClinicalTrials.gov on 19 February 2021 (NCT04762433) and is not yet recruiting.