Design of a Mobile App to Monitor and Control in Real Time Type 2 Diabetes Mellitus in Peru

Ocares-Cunyarachi, Lilian

doi:10.3991/ijim.v17i10.38207

Cited by 3 publications

(2 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The AUC ranges from 0 to 1 and is often used to measure a model's accuracy in identifying outcomes using the AUC metric. A larger AUC indicates superior performance [34].…”

Section: The Variance Of Each Group Is Homogenousmentioning

confidence: 99%

Assessing Subjective Visual Vertical Reliability: A Comparison of the “Bucket Test,” a Mobile App, and a Virtual System

Waly,

Alshammari,

Alshammari

et al. 2024

Int. J. Onl. Eng.

View full text Add to dashboard Cite

The subjective visual vertical (SVV) is a potential indicator of vestibular dysfunction as it assesses an individual’s perception of a vertical line. Despite this, and as a result of specific logistical impediments, SVV has not entered standard clinical practice. Dizziness is the third most common clinical complaint by patients (20%) in outpatient offices. It adversely affects the patient’s life and is often accompanied by intensive healthcare. This study aims to determine whether the bucket test and mobile phone app are as reliable as the Virtual SVV system in assessing the SVV. This study involves four types of investigation to determine the relationship or difference among three tests, including their performance comparison, descriptive analysis, one-way ANOVA test, receiver operating characteristic (ROC) curve, and correlation analysis. After organizing the raw data from 207 healthy volunteer participants for 8 trials, it was found that 59% were female and 41% were male. The data was analyzed utilizing the SPSS program. The test performance is measured using the ROC curve, and the results indicate that the bucket with the highest ROC coefficient is 0.72.

show abstract

“…The AUC ranges from 0 to 1 and is often used to measure a model's accuracy in identifying outcomes using the AUC metric. A larger AUC indicates superior performance [34].…”

Section: The Variance Of Each Group Is Homogenousmentioning

confidence: 99%

Assessing Subjective Visual Vertical Reliability: A Comparison of the “Bucket Test,” a Mobile App, and a Virtual System

Waly,

Alshammari,

Alshammari

et al. 2024

Int. J. Onl. Eng.

View full text Add to dashboard Cite

show abstract

“…From this perspective, M-Thyroid Care stands out as a promising prototype mobile application designed exclusively for thyroid clinics. Its primary goal is to transform healthcare by enabling virtual video call-based consultations, thereby minimizing unnecessary in-person visits for thyroid patients [11]. M-Thyroid Care enables patients and healthcare professionals to participate in virtual consultations, initiate dynamic chat sessions, and easily exchange important files, videos, and photographs.…”

Section: Introductionmentioning

confidence: 99%

M-Thyroid Care Mobile App: Virtual Video Consultation Application for Thyroid Clinic

Noorulsadiqin Azbiya Yaacob,

Ahmad Hanis Mohd Shabli,

Noor Rafhati Adyani Abdullah

2024

Int. J. Interact. Mob. Technol.

View full text Add to dashboard Cite

The present study aims to enhance thyroid clinics by proposing solutions through collaboration between medical experts and researchers, thereby enhancing the quality of healthcare services. To minimize unnecessary in-person consultations, a doctor requested the development of an app to address non-critical physical consultation appointments. Design-based research is a robust methodology that combines theory-driven inquiry with real-world problem-solving to develop interventions or serve as the basis for the research being discussed. M-Thyroid Care is designed to provide a practical and cost-effective platform for online consultations, facilitating video calls between patients and doctors. By leveraging this technology, the app aims to enhance patient monitoring and optimize the efficiency of thyroid clinic consultations. Moreover, the integrated chat feature allows for real-time communication, fostering effective doctor-patient interaction even outside of scheduled appointments. Additionally, the app enables the sharing of files, videos, and images, empowering doctors to review diagnostic reports and relevant visual data remotely. This further streamlines the consultation process. By reducing the reliance on physical visits for non-critical cases, the app has the potential to enhance access to specialized care, decrease wait times, and optimize resource utilization in the clinic setting. The prototype has the potential to enhance patient care, as demonstrated by this proactive engagement with stakeholders.

show abstract

User Acceptability Testing of Mobile Application in Indian Local Languages for Cardiovascular Risk Stratification and Modification among Patients with Type 2 Diabetes

Erande,

Ray Mohanty,

Rai

2024

International Journal of Innovative Science and Research Techno

View full text Add to dashboard Cite

Introduction: Cardiovascular disease is the leading cause of death in patients with type 2 diabetes. Digital health tools like mobile application have fast emerged as a technology capable of closing the gap in cardiovascular disease self- management and revolutionizing the way healthcare is traditionally delivered. One of the causes for low app engagement of Apps in India is perhaps that few of these apps are available in local languages. The goal is to reach as many diabetic patients as possible while avoiding linguistic hurdles.  Methodology: The ‘healthy heart’ mobile app was developed and translated into Hindi and Marathi languages for CVD risk stratification and risk management among Type 2 diabetes mellitus patients. User acceptability testing of the app on its design, presentation, content, and user- friendliness was undertaken. The feedback on utility of the app for CVD risk stratification and modification was assessed. A total 100 multilingual app users profile were noted for CVD Risk Status, Life Style Practices and CVD Risk Factors.  Results: The Healthy Heart multi-lingual app was successfully developed for CVD risk classification and risk management among Type 2 diabetes mellitus patients. The patients had the choice to select the desired language of the app from the versions available in English, Hindi and Marathi. The Mobile App's Home Screen displayed the CVD risk score and category, a health tracker to monitor compliance with WHO recommendations regarding diet, physical activity, addictions, medication adherence, diabetic, and CVD Risk Profile. The majority of respondents rated the App's design, presentation, content, and user- friendliness favorably and emphasized the utility of App for CVD self-management and risk reduction. Characteristics of Type 2 Diabetic patients demonstrated poor compliance for total fruits and vegetable intake, total fat intake and total salt intake, physical activity Guidelines apart from poor control for blood pressure, glycemic control and lipid targets.  Conclusion: The multilingual mobile App for CVD risk stratification, self-management and CVD risk reduction among diabetic patients was successfully developed in Hindi and Marathi language. User acceptability testing results were found to be favorable for the mobile app.

show abstract

Design of a Mobile App to Monitor and Control in Real Time Type 2 Diabetes Mellitus in Peru

Cited by 3 publications

References 26 publications

Assessing Subjective Visual Vertical Reliability: A Comparison of the “Bucket Test,” a Mobile App, and a Virtual System

Assessing Subjective Visual Vertical Reliability: A Comparison of the “Bucket Test,” a Mobile App, and a Virtual System

M-Thyroid Care Mobile App: Virtual Video Consultation Application for Thyroid Clinic

User Acceptability Testing of Mobile Application in Indian Local Languages for Cardiovascular Risk Stratification and Modification among Patients with Type 2 Diabetes

Contact Info

Product

Resources

About