Mobile Medical Applications Research Articles

The combined effect of behavioural activation system and perceived anthropomorphism on individuals’ intention to use digital therapeutics tools for asthma and respiratory-related diseases

ABSTRACT The integration of Digital Therapeutics (DTx) is profoundly transforming patients’ care management. Original combinations of IoT medical devices and related mobile applications resulting in DTx, may boost patients’ engagement and adherence to treatment regimens, resulting as ‘intelligent’ assistants in patients’ health recovery. In this paper we conducted a study among a sample of 507 participants by setting a prototype of DTx able to monitor respiratory-related diseases as a setting. Results demonstrated that individuals’ perceived product intelligence of such digital tools led to higher intention to use, through the effect of their Behavioural Activation System, that is, the psychological mechanism influencing their motivation towards engaging in rewarding and goal-directed behaviours. Moreover, individuals’ perceived anthropomorphism of these tools, in terms of individuals’ tendency attribute human-like characteristics or emotions to non-human entities such in these technological tools, increase such effect.

Raising Awareness of Mistreatment Policies and Reporting Procedures Using a Novel Medical Student Mobile Application.

Reports of mistreatment are an important first step to improving medical students' learning environment. Students may not report mistreatment due to a lack of awareness of institutional policies, reporting procedures, or for fear of reprisal. We sought to determine if a medical school cross-platform mobile application (app) could be used to improve students' awareness of mistreatment policies and procedures. Participants in this intervention included Drexel University College of Medicine (DUCOM) medical students, faculty, and Student Affairs Deans. We created the DUCOMpass© app to make mistreatment policies and procedures more readily available and to ease mistreatment reporting for medical students. To determine the efficacy of the app at raising mistreatment awareness, we analyzed our institutional GraduationQuestionnaire data before and after the introduction of the app (from 2016 to 2023) as compared with the national average. We verified our students' self-reported data with app usage data. To our knowledge, this is the first instance of a medical school mobile app being implemented to successfully address medical student mistreatment awareness and reporting. We found that reaching students in a familiar and easily accessible mode(s) of communication is a catalyst for lasting change. Not applicable.

The problems related to implementation of AI into health care system: A review

The AI technologies are more and more widely implemented into modern health care. the mobile medical applications permit to monitor course of chronic diseases and form healthier behavior in patients, to reduce number of visits to medical organizations and to improve accessibility of medical care for limited mobile patients. However, actually there are number of problems limiting implementation of AI into functioning of health services. The article discusses problems associated with computer technologies themselves and medical research using them. The ethical nuances of widespread application of AI are described. The modes of overcoming existing disadvantages of computer and mobile health care are proposed.

Разработка мобильного приложения для виртуальных медицинских консультаций с использованием Xamarin

The paper discusses technologies for developing a medical mobile application with the function of virtual online consultations. It was revealed that applications with the function of online consultations in medicine are relevant and meet the requirements of modern telemedicine. The article analyzes native and cross-platform development technologies. The use of software for developing a mobile application with an online consultation function is justified: C#, Xamarin, XAML, MS SQL, SignalR library. The benefits of using Xamarin have been identified. An algorithm for developing a mobile application for virtual medical consultations is considered.

Healthcare Analysis Based on Diabetes Prediction Using a Cuckoo-Based Deep Convolutional Long-Term Memory Algorithm

In recent years, the demand for mobile medical applications utilizing the Internet of Things (IoT) for diabetes diagnosis has been progressively increasing. Diabetes is commonly known as a chronic illness that presents a significant danger to individuals, analysing when blood sugar levels surpass the typical range. If diabetes is not promptly treated, hyperosmolar conditions can lead to serious health issues like hyperglycaemia and possibly even death. Since early detection enables lifestyle changes that prevent the disease's progression, it is crucial for diabetes management and health systems. However, diabetes diagnosis has a long computational time and low prediction accuracy. To address this issue, we propose a Cuckoo-Based Deep Convolutional Long-Term Memory (CDC-LSTM) algorithm that increases accuracy by classifying diabetics or non-diabetics. Additionally, we utilize the Standardized Feature Scaler (SFS) method to normalize the variance data by removing the mean of each feature. Moreover, we select the optimal features in the diabetes dataset utilising the Filter-Based Decision Tree (FBDT) technique. Finally, the proposed CDC-LSTM method can be used to distinguish between diabetics and non-diabetics, improving the accuracy of identifying diabetic patients. Additionally, the proposed method can predict diabetes using performance assessments such as precision, recall, and F-measure. Furthermore, the method's accuracy can be improved to 95.18% compared to previous approaches.

Design of Medical Mobile Application for Prediction of Medical Security Issues in Health Care

Design of Medical Mobile Application for Prediction of Medical Security Issues in Health Care

Usage and attitude of medical students towards mobile medical applications during and after COVID-19 lockdown: repeated cross-sectional study

BackgroundCOVID-19 pandemic has accelerated the shift toward e-learning, particularly in medical education. Mobile medical applications (apps) have become integral tools for e-learning due to the prevalence of smartphones among medical students. Therefore, we aim to assess the usage and attitude of undergraduate Egyptian medical students towards mobile medical apps during and after the COVID-19 lockdown.MethodsThis is a two-phase repeated cross-sectional study using an online, pilot-tested, and self-administered survey conducted at the Faculty of Medicine, Menoufia University, Egypt. Phase 1 was during the academic year 2019–2020 (during lockdown), and phase 2 was during the academic year 2021–2022 (after lockdown). Out of the 4800-target population for each phase, a sample size of 140 medical students was randomly selected from each study year, resulting in a total sample size of 840 students for all six academic and clinical years for each phase.ResultsA total of 566 students in phase 1 and 616 students in phase 2 responded to the survey, with response rates of 67.62% and 73.33%, respectively. In phase 1, 55.7% of students reported using medical apps, with no significant difference between males and females (60.1% vs. 53.8%; p = 0.17) or between academic and clinical years (56.3% vs. 54.7%; p = 0.7). In phase 2, the percentage increased to 70.9%, with a significant difference between males and females (80% vs. 62.9%; p < 0.001) and between academic and clinical years (79.8% vs. 63%; p < 0.001). Medical dictionaries were the most commonly used apps, whereas medical calculators were the least common in both phases. Regarding their attitude, most students (65.1% and 73.9% in phases 1 and 2, respectively) expressed confidence in using medical apps, while 81.3% in phase 1 and 88.1% in phase 2 agreed that using medical apps is a flexible method of learning. Lack of knowledge regarding which app to download was the most reported cause of limitation in medical app usage by 37.8% of the students in phase 1 and 40% in phase 2.ConclusionOur study revealed that the COVID-19 lockdown led to a significant increase in the use of mobile medical apps among Egyptian medical students. Despite the positive attitude of students towards these apps, multiple challenges still need to be addressed to ensure their optimal utilization in medical education.

Effectiveness of IMPUTE ADT-1 mobile application in children with autism spectrum disorder: An interim analysis of an ongoing randomized controlled trial.

IMPUTE Inc., a software firm dedicated to healthcare technology, has developed a mobile medical application known as IMPUTE ADT-1 for children with autism spectrum disorder (ASD) based on the principle of applied behavior analysis. The primary objective of this trial was to compare the efficacy of add-on treatment with IMPUTE ADT-1 in children with ASD aged two to six years as compared to standard care alone for 12 weeks (in terms of change in Autism Diagnostic Observation Schedule [ADOS-2] scores). The secondary objective of the study was to assess the compliance with IMPUTE ADT-1 among participants and also to evaluate the feedback of parents regarding IMPUTE ADT-1 at the end of 12 weeks. The application provides personalized programs tailored to each user's needs, and the program evolves based on the user's progress. It also utilizes face tracking, eye tracking, and body tracking to gather behavior-related information for each child and apply it in reinforcement learning employing artificial intelligence-based algorithms. Till the time of interim analysis, 37 and 33 children had completed 12-week follow-up in IMPUTE ADT-1 and control arm. At 12 weeks, as compared to baseline, change in social affect domain, repetitive ritualistic behavior domain, total ADOS-2 score, and ADOS-2 comparison score was better in the intervention group as compared to the control group (P < 0.001 for all). A total of 30 (81%), 28 (75%), and 29 (78%) caregivers in the IMPUTE ADT-1 group believed that the ADT-1 app improved their child's verbal skills, social skills, and reduced repetitive behavior, respectively. IMPUTE ADT-1 mobile application has the efficacy to improve the severity of autism symptoms in children. Parents of these children also feel that the application is beneficial for improving the socialization and verbal communication of their children.

Medical Mobile Application for The Management of Heart-Lung Machine during Cardiac Surgery

The goal of this work is to construct a mobile application device that has a wide variety of functions which has clinical planning and decision making for heart-lung machine controlling and to assess the users’ level of satisfaction. The app was constructed according to the steps of design, algorithm, and validation, which is based on the ionic framework. The levels of satisfaction with the developed mobile app among 20 perfusionists were assessed by a questionnaire. The project researchers have officially assigned this medical mobile application with the name is Perfusion Assistant app. that can be accessed and used effectively cross platform on iOS and Android. The application is comprised of 5 main categories which includes: a perfusion calculator, myocardial protection chart, drugs details, priming solution, and parameters values. This finding shown that all cardiovascular parameters did not significant differ from Perfusion Assistant app. when compared to manual calculation. User’s satisfaction was at 3.64 ± 0.76 in the first evaluation. After modification with feedback from experts, the satisfaction of this application was evaluated with a 4.13 ± 0.56. Thereby, Perfusion Assistant app. is an application designed in clinical planning and decision of heart-lung machine controlling for perfusionists and medical staff that work in an opened heart surgery arena. Perfusion Assistant app. offers a variety of calculations related to cardiopulmonary bypass including blood flow rate, systemic vascular resistant, priming volume, and predicted hematocrit. Furthermore, Perfusion Assistant app. provides a quick, easy access, and real-time application for cardiopulmonary bypass that user’s satisfaction was a good level.

Influence of doctor-patient trust on the adoption of mobile medical applications during the epidemic: a UTAUT-based analysis.

This study examines the factors influencing users' intention to continue using mobile medical apps within the framework of the Unified Theory of Acceptance and Use of Technology (UTAUT) model. Through a combination of questionnaire surveys and interviews, the research finds that doctor-patient trust, Performance Expectancy (PE), social influence, and facilitating conditions significantly impact users' intention to utilize mobile medical apps. Furthermore, the study reveals the moderating effect of doctor-patient trust on social influence, indicating an increased trust level during the epidemic, attributed to positive media coverage, complimentary medical services, and risk-sharing initiatives. These results provide valuable insights for the field of internet healthcare, COVID-19 response strategies, health information management, and the advancement of digital health technologies, spotlighting the pivotal roles of trust, PE, and social influence in fostering sustained engagement with mobile health apps.

Mobile applications in radiology: own study based on polish data

As the number of smartphones increases, so does the number of medical apps. Medical mobile applications are widely used in many medical fields by both patients and doctors. However, there are still few approved mobile applications that can be used in the diagnostic-therapeutic process and radiological apps are affected as well. We conducted our research by classifying radiological applications from the Google Play® store into appropriate categories, according to our own qualification system developed by researchers for the purposes of this study. In addition, we also evaluated apps from the App Store®. The radiology application rating system we created has not been previously used in other articles. Out of 228 applications from the Google Play store, only 6 of them were classified as “A” category with the highest standard. Apps from the App Store (157) were not categorized due to the lack of download counts, which was necessary in our app-rating system. The vast majority of applications are for educational purposes and are not used in clinical practice. This is due to the need of obtaining special permits and certificates from relevant institutions in order to use them in medical practice. We recommend applications from the Google Play store that have been classified in the “A” category, evaluating them as the most valuable. App Store apps data is described and presented in the form of diagrams and tables.

Usability of the medical mobile application for patients: Kazakhstani case

Object: Covid-19 pandemic was impact in all aspects of our life, especially digital health care. This study was aimed to examine the usability of the state medical mobile application called Damumed with neuromarketing tool – eye-tracking. Damumed is the main state health information system designed to facilitate the work of medical personnel, thereby improving the quality and accessibility of medical services for patients, where patients can find all medical appointments, health passport and all health-related information. This research is aimed to achieve SIG Goal of Good health and well-being for people.Methods. Using neuromarketing instrument with unstructured interviews to identify key features of usability aspects of the medical mobile application.Findings: Overall, 23 patients were separated into 2 age groups of young (18-24) and adults (35-44). They engaged in the study to participate both in neuromarketing research and unstructured interviews. Adults had difficulties in understanding the navigation of the app, while younger group could navigate in the app intuitively.Conclusions. Neuromarketing studies and individual interviews clarified assessing the usability of the medical mobile application interface. Since the respondents have different background, for adults it was a bit challenging to assess the app’s interface. In this respect, for older generation would a barrier to adopt this kind of information systems.

Medical Factors-Based Mobile Application for Choosing Contraceptives: A Data Mining Approach

Medical Factors-Based Mobile Application for Choosing Contraceptives: A Data Mining Approach

A-60 Gender and Age Differences on the Sway Medical Mobile Balance Test

Abstract Purpose To determine if performance on the Sway Medical Mobile Application Balance Test differs by age and gender. Methods Pre-season baseline data from 33,784 individuals (51.3% girls/women) between ages 12 and 22 (mean=16.8 years, SD=2.5), tested in the summer of 2022, without a self-reported concussion in the past 6 months, and without self-reported ADHD were examined. Three Spearman correlations were used to assess the association between balance scores and age for the total sample, and for the boys/men and girls/women groups separately. Twelve Mann-Whitney U tests were used to compare genders on balance scores within each age group (12, 13, 14, through 22-years-old) and for the total sample. A Bonferroni correction was used to adjust for multiple comparisons, and the level of significance was set at p=0.004. Results There was a positive correlation between higher (i.e., better) balance scores and older age for the total sample (r=.25, p&amp;lt;.001), and within the boys/men (r=.30, p&amp;lt;.001) and girls/women groups separately (r=.21, p&amp;lt;.001). For every age, there was a significant difference between boys/men and girls/women on balance test scores, with girls/women obtaining higher (i.e., better) balance scores than boys/men. Effect sizes for these differences ranged from small to medium (Hedge’s g=.29-.65). Conclusions There are age and gender-related differences on baseline Sway Medical Mobile Balance Test scores. Girls/women performed better on the balance testing compared to boys/men at all ages. Additionally, the balance scores improved throughout adolescence and generally plateaued in early adulthood (18-22-years-old).

Semantic web-based diagnosis and treatment of vector-borne diseases using SWRL rules

Vector-borne diseases (VBDs) are a kind of infection caused through the transmission of vectors generated by the bites of infected parasites, bacteria, and viruses, such as ticks, mosquitoes, triatomine bugs, blackflies, and sandflies. If these diseases are not properly treated within a reasonable time frame, the mortality rate may rise. In this work, we propose a set of ontologies that will help in the diagnosis and treatment of vector-borne diseases. For developing VBD’s ontology, electronic health records taken from the Indian Health Records website, text data generated from Indian government medical mobile applications, and doctors’ prescribed handwritten notes of patients are used as input. This data is then converted into correct text using Optical Character Recognition (OCR) and a spelling checker after pre-processing. Natural Language Processing (NLP) is applied for entity extraction from text data for making Resource Description Framework (RDF) medical data with the help of the Patient Clinical Data (PCD) ontology. Afterwards, Basic Formal Ontology (BFO), National Vector Borne Disease Control Program (NVBDCP) guidelines, and RDF medical data are used to develop ontologies for VBDs, and Semantic Web Rule Language (SWRL) rules are applied for diagnosis and treatment. The developed ontology helps in the construction of decision support systems (DSS) for the NVBDCP to control these diseases.

Mobile Applications for Resting Tremor Assessment in Parkinson's Disease: A Systematic Review.

(1) Background: Resting tremor is a motor manifestation present in most Parkinson's disease (PD) patients. For its assessment, several scales have been created, but mobile applications could help in objectively assessing resting tremor in PD patients in person and/or remotely in a more ecological scenario. (2) Methods: a systematic review following the PRISMA recommendations was conducted in scientific databases (PubMed, Medline, Science Direct, Academic Search Premier, and Web of Science) and in the main mobile application markets (Google Play, iOS App Store, and Windows Store) to determine the applications available for the assessment of resting tremor in patients with PD using only the measurement components of the phone itself (accelerometers and gyroscopes). (3) Results: 14 articles that used mobile apps to assess resting tremor in PD were included, and 13 apps were identified in the mobile application markets for the same purpose. The risk of bias and of applicability concerns of the articles analyzed was low. Mobile applications found in the app markets met an average of 85.09% of the recommendations for the development of medical mobile applications. (4) Conclusions: the use of mobile applications for the evaluation of resting tremor in PD patients has great potential, but validation studies for this purpose are scarce.

PS-C20-3: MOBILE MEDICAL APP CAN BE MORE EFFECTIVE IN LONG-TERM MANAGEMENT OF HYPERTENSION PATIENTS

Objective: The application of mobile medical application, APP, to manage patients with hypertension makes the contact between doctors and patients more convenient, saves the economic cost and time cost of patients, and also makes it easier for doctors to manage patients and improve their compliance. This study investigated the effect of APP on long-term management of hypertension patients. Design and method: This trial was a randomized, single-blind, parallel, controlled study. A total of 302 patients with hypertension were included in this study and observed for one year. All the enrolled patients received antihypertensive treatment of nifedipine controlled release tablets with or without telmisartan in outpatient or ward. The APP of the experimental group could be used to push health education information, remind patients to measure their own blood pressure and take medication, and consult doctors online. Blood pressure, improvement of hypertensive target organ injury, and sodium intake were assessed in both groups after one year treatment. Results: There were no significant differences in blood pressure, urinary microalbumin and 24-hour urinary sodium levels between the two groups at baseline. APP information push was more helpful to the control of blood pressure, systolic and diastolic blood pressure decreased significantly, after treatment, systolic blood pressure of experimental group vs control group 133 ± 6mmHg vs 141 ± 11mmHg, P &lt; 0.05; Diastolic pressure 83 ± 7mmHg vs 89 ± 9mmHg, P &lt; 0.05. APP information push was more helpful to improve target organ injury (decrease of microalbuminuria), and microalbuminuria after treatment was 31 ± 12 mg/L vs 47 ± 14 mg/L, P &lt; 0.05. APP information push helped control sodium intake, and the urine sodium level at 24 hours after treatment was 123 ± 31 mmol/24 h vs 148 ± 28 mmol/24 h, P &lt; 0.05. Conclusions: Using mobile medical APP for patient management can help control patients’ blood pressure level, improve the degree of renal damage caused by hypertension, and help control sodium intake. APP can be used as an auxiliary means for long-term management of hypertension patients, which can improve the quality of blood pressure management of patients more effectively, conveniently and economically.

Features and Functionalities of Medical Mobile Applications for the Endemic Phase of COVID‐19: Review and Content Analysis

The study's objective was to assess the features and content of the COVID-19 mobile applications accessible in the Apple AppStore. A content analysis, comparison, and functionality evaluation of a few COVID-19 related mobile applications was performed. The search for COVID -19 related apps in the iOS AppStore took place between February 1 and March 31, 2022. The mobile applications received a maximum of 7 points (basic feature assessment) and 8 points overall (functionality assessment). The requirements were fully met by receiving one point. Frequencies from descriptive statistics were used to allude to the applications' features according to the app's basic purpose. A total of 234 applications were recognized using the keywords to exploreCOVID-19 related mobile applications in Apple AppStore. However, 58 mobile applications (24.8%) relevant to COVID-19 were evaluated. According to the findings of an evaluation of basic aspects of mobile applications, 89.7% require an internet connection, 70.7% have a size of less than 50 MB, 96.6% require no funding, 58.6% include educational content, and 60.3% offer advice from the applications. In terms of score, 41.4% scored three or below, whereas 58.6% scored four or above. Functionality assessment wise, 79.3% included information regarding COVID-19, 12.1% included COVID-19 contact tracing, 17.2% had vaccination status, a health authority maintained 50%, 31.0% included COVID-19 statistics, and 25.8% were able to report ART/PCR test. In terms of score, 91.4% scored three points or less, and 8.6% scored four points or more. This study has discovered several applications that could effectively prevent COVID-19 pandemic spread. Based on the findings, mobile applications that would be recommended are the ones supported by the government health administration of the respective country. App development companies’ applications show that competent healthcare personnel was not involved in developing the applications. Online consultation with healthcare professionals might help the public who do not have access to the nearest hospital.

The Role of Individual Factors in Users’ Intentions to Use Medical Tourism Mobile Apps

The successful operation of medical tourism mobile applications primarily depends on the extent to which users are fully motivated to adopt their use. Therefore, the primary purpose of this study was to investigate the factors influencing medical tourism mobile application usage intentions. This study applied the unified theory of acceptance and use of technology (UTAUT2) to build a comprehensive model that explains users’ intentions to use medical tourism mobile apps. Our research findings confirm the validity of the UTAUT2 in explaining users’ intentions to use medical tourism mobile apps in the context of medical tourism mobile services. Additionally, the results focus on the enhancement in the role of the other rather that contextual attributes of the IT/IS environment (i.e., personal involvement and personal innovativeness). This study can confirm the importance of the UTAUT2 constructs in the setting of medical tourism mobile app usage. By conducting surveys, medical tourism mobile app designers can know that personal involvement and personal innovativeness lead to influences on the effectiveness of corporate marketing efforts relating to using mobile medical apps.

UI Design of Medical Check-Up Information System at Pratama Clinic Based on Design Thinking Method

Medical Chek Up (MCU) or Periodic health checks are part of occupational health services that are the right of every worker and as part of preventing health risks to all workers and to reduce the risk of sudden death due to illness in the workplace, it is necessary to carry out annual periodic health checks as a worker obligation that must be carried out once a year. The purpose of this study was to design the User Interface (UI) of the Medical Check-Up Mobile application to make it easier for workers to find out the results of their examinations and doctors can evaluate the health status of workers. The object of this study was carried out at the Pratama Clinic of PT. Pertamina Patra Niaga Sub Holding Marketing Region Sumbagsel. The research method in this study is a descriptive method that is usually used to solve problems, by describing and describing the classified data. While the design method used is Design Thinking. The results of the User Interface design can later be used as a proposal to the Pratama Clinic of PT Pertamina Patra Niaga Subholding Marketing Sumbagsel Region for further implementation by the Internal IT Team.