Barriers and Drivers Regarding the Use of Mobile Health Apps Among Patients With Type 2 Diabetes Mellitus in the Netherlands: Explanatory Sequential Design Study

A Culturally Sensitive Mobile App (DiaFriend) to Improve Self-Care in Patients With Type 2 Diabetes: Development Study

BACKGROUND

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.

OBJECTIVE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Identification of challenges and leveraging mHealth technology, with need-based solutions to empower self-management in type 2 diabetes: a qualitative study

INTRODUCTION

Effective diabetes management relies mainly on an individual's ability to perform self-care tasks. However, this process is influenced by a complex interplay of factors. This study explores the multifaceted influences on Diabetes Self-Management (DSM), examining both factors influencing and affecting DSM. Understanding these influences is crucial for developing targeted Digital Health Interventions that empower individuals with diabetes to achieve successful self-management.

OBJECTIVES

To identify problems faced by Type 2 Diabetes Mellitus (T2DM) individuals in self-managing diabetes and leveraging mHealth technology, with need-based solutions to Empower Self-Management in T2DM.

METHODOLOGY

In-depth semi-structured interviews were conducted among ten patients with T2DM visiting the outpatient department of a tertiary care hospital in coastal Karnataka. Additionally, six healthcare professionals (HCPs) working closely with T2DM patients were interviewed to understand their perspectives on using mHealth to manage T2DM effectively. The themes for the solutions described were analyzed using ATLAS-TI software.

RESULTS

Our research examined certain factors that might have influenced effective diabetes self-management and investigated patient perspectives on using digital health solutions in diabetes self-management. This study found that technology skills, duration of diabetes, knowledge, and personal beliefs were all significant factors affecting self-management in participants with T2DM. Additionally, socioeconomic factors were also seen to influence effective diabetes self-management. The Google search engine was used by 50% of the participants interviewed to learn about T2DM. Diet management through Google searches was used by a minority (30%) of the patients. None of the participants had previously used any mobile health applications (mHealth apps) to manage T2DM. 20% of the participants expressed limited knowledge about using smartphones or wearables to track health parameters. The study also identified potential non-technological barriers to mHealth adoption. To address these concerns, researchers used an empathy map to develop solutions that promote mHealth use.

CONCLUSION

Several challenges and need-based mHealth solutions were identified to empower diabetes self-management education among T2DM patients. Implementing need-based mHealth solutions such as data tracking, personalized feedback, and access to educational resources can lead to better disease control and a higher quality of life for those with T2DM. Further research and development in mHealth interventions, and collaborative efforts among healthcare providers, patients, and technology developers, hold a promising future for the healthcare sector in providing efficient, effective, and accessible care.

Effects of an Electronic Medical Records-Linked Diabetes Self-Management System on Treatment Targets in Real Clinical Practice: Retrospective, Observational Cohort Study

BACKGRUOUND

This study evaluated the effects of a mobile diabetes management program called "iCareD" (College of Medicine, The Catholic University of Korea) which was integrated into the hospital's electronic medical records system to minimize the workload of the healthcare team in the real clinical practice setting.

METHODS

In this retrospective observational study, we recruited 308 patients. We categorized these patients based on their compliance regarding their use of the iCareD program at home; compliance was determined through self-monitored blood glucose inputs and message subscription rates. We analyzed changes in the ABC (hemoglobin A1c, blood pressure, and low-density lipoprotein cholesterol) levels from the baseline to 12 months thereafter, based on the patients' iCareD usage patterns.

RESULTS

The patients comprised 92 (30%) non-users, 170 (55%) poor-compliance users, and 46 (15%) good-compliance users; the ABC target achievement rate showed prominent changes in good-compliance groups from baseline to 12 months (10.9% vs. 23.9%, P<0.05), whereas no significant changes were observed for poor-compliance users and non-users (13.5% vs. 18.8%, P=0.106; 20.7% vs. 14.1%, P=0.201; respectively).

CONCLUSION

Implementing the iCareD can improve the ABC levels of patients with diabetes with minimal efforts of the healthcare team in real clinical settings. However, the improvement of patients' compliance concerning the use of the system without the vigorous intervention of the healthcare team needs to be solved in the future.

Living with my diabetes - introducing eHealth into daily practices of patients with type 2 diabetes mellitus

Objective

Diabetes patients can draw on an increasing number of eHealth apps to support them in the self-management of their disease. While studies so far have focused on patients with type 1 diabetes, we explored how patients with type 2 diabetes mellitus (T2DM) integrate eHealth apps into their practices aimed at managing and coping with the disease, which aspects were considered particularly valuable and which challenges users encountered.

Methods

Semi-structured interviews and focus group sessions were conducted to explore how patients cope with T2DM in their daily lives and their attitude towards eHealth. In a further step, four eHealth apps were tested by patients and their expectations and experiences studied by way of qualitative interviews and focus groups.

Results

The analysis showed that the study participants valued in particular the possibility to use eHealth apps to sense and gain a better understanding of their own body, to learn about specific responses of their body to nutrition and physical activity, and to support changes in daily routines and lifestyle. Key challenges encountered related to difficulties in interpreting the data, matching the data to other bodily sensations, getting overly occupied with the disease and difficulties in integrating the apps into personal, family, and care practices.

Conclusion

Under certain conditions, eHealth can play an important role for patients in developing a nuanced, personal understanding of their body and coping with T2DM. A prerequisite is that eHealth needs to be fitted into the specific practices of users, and patients desire a strong role by their care professionals in providing support in interpretation of data.

Adoption of Wearable Insulin Biosensors for Diabetes Management: A Cross-Sectional Study

BACKGROUND

Wearable insulin biosensors represent a novel approach that combines the benefits of real-time glucose monitoring and automated insulin delivery, potentially revolutionizing how individuals with diabetes manage their condition.

STUDY PURPOSE

To analyze the behavioral intentions of wearable insulin biosensors among diabetes patients, the factors that drive or hinder their usage, and the implications for diabetes management and healthcare outcomes.

METHODS

A cross-sectional survey design was adopted in this study. The validated questionnaire included 10 factors (Performance expectancy, effort expectancy, social influence, facilitating conditions, behavioral intention, trust, perceived privacy risk, and personal innovativeness) affecting the acceptance of wearable insulin sensors. A total of 248 diabetic patients who had used wearable sensors participated in the study.

RESULTS

Performance expectancy was rated the highest (Mean = 3.84 out of 5), followed by effort expectancy (Mean = 3.78 out of 5), and trust (Mean = 3.53 out of 5). Statistically significant differences (p < 0.05) were observed with respect to socio-demographic variables including age and gender on various influencing factors and adoption intentions. PE, EE, and trust were positively associated with adoption intentions.

CONCLUSION

While wearable insulin sensors are positively perceived with respect to diabetes management, issues like privacy and security may affect their adoption.

Overcoming the struggle of living with type 2 diabetes - diabetes specialist nurses' and patients' perspectives on digital interventions

BACKGROUND

Diabetes self-management education and support (DSMES) is a cornerstone in the treatment of type 2 diabetes mellitus (T2DM). It is unclear whether delivering DSMES as a digital health intervention (DHI) might meet the needs experienced by patients with T2DM and diabetes specialist nurses (DSN) of the primary health care system in Sweden.

METHODS

Fourteen patients with T2DM and four DSN participated in three separate focus groups: two groups comprised patients and one group comprised DSN. The patients discussed the questions: "What needs did you experience after your T2DM diagnosis?" and "How might these needs be met with a DHI?" The DSN discussed the questions: "What needs do you experience when treating a patient with newly diagnosed T2DM?" and "How might these needs be met with a DHI?". Furthermore, data were collected in the form of field notes from group discussions at a meeting including 18 DSNs working with T2DM in PHCCs. The discussions from focus groups were transcribed verbatim and analyzed together with the field notes from the meeting using inductive content analysis.

RESULTS

The analysis yielded the overall theme: "Overcoming the struggle of living with T2DM", which was summarized in two categories: "learning and being prepared" and "giving and receiving support". Important findings were that, for success, a DHI for DSMES must be integrated into routine care, provide structured, high-quality information, suggest tasks to stimulate behavioral changes, and provide feedback from the DSN to the patient.

CONCLUSION

This study highlighted several important aspects, from the perspectives of both the patient with T2DM and the DSN, which should be taken into consideration for the successful development and use of a DHI for DSMES.

Mobile Health Apps for the Control and Self-management of Type 2 Diabetes Mellitus: Qualitative Study on Users' Acceptability and Acceptance

BACKGROUND

Mobile health apps are promising tools to help patients with type 2 diabetes mellitus (T2DM) improve their health status and thereby achieve diabetes control and self-management. Although there is a wide array of mobile health apps for T2DM available at present, apps are not yet integrated into routine diabetes care. Acceptability and acceptance among patients with T2DM is a major challenge and prerequisite for the successful implementation of apps in diabetes care.

OBJECTIVE

This study provides an in-depth understanding of the perceptions of patients with T2DM before use (acceptability) and after use (acceptance) regarding 4 different mobile health apps for diabetes control and self-management.

METHODS

A descriptive qualitative research design was used in this study. Participants could choose 1 of the 4 selected apps for diabetes control and self-management (ie, Clear.bio in combination with FreeStyle Libre, mySugr, MiGuide, and Selfcare). The selection was based on a systematic analysis of the criteria for (functional) requirements regarding monitoring, data collection, provision of information, coaching, privacy, and security. To explore acceptability, 25 semistructured in-depth interviews were conducted with patients with T2DM before use. This was followed by 4 focus groups to discuss the acceptance after use. The study had a citizen science approach, that is, patients with T2DM collaborated with researchers as coresearchers. All coresearchers actively participated in the preparation of the study, data collection, and data analysis. Data were collected between April and September 2021. Thematic analysis was conducted using a deductive approach using AtlasTi9.

RESULTS

In total, 25 coresearchers with T2DM participated in this study. Of them, 12 coresearchers tested Clear, 5 MiGuide, 4 mySugr, and 4 Selfcare. All coresearchers participated in semistructured interviews, and 18 of them attended focus groups. Personal health was the main driver of app use. Most coresearchers were convinced that a healthy lifestyle would improve blood glucose levels. Although most coresearchers did not expect that they need to put much effort into using the apps, the additional effort to familiarize themselves with the app use was experienced as quite high. None of the coresearchers had a health care professional who provided suggestions on using the apps. Reimbursement from insurance companies and the acceptance of apps for diabetes control and self-management by the health care system were mentioned as important facilitating conditions.

CONCLUSIONS

The research showed that mobile health apps provide support for diabetes control and self-management in patients with T2DM. Integrating app use in care as usual and guidelines for health care professionals are recommended. Future research is needed on how to increase the implementation of mobile health apps in current care pathways. In addition, health care professionals need to improve their digital skills, and lifelong learning is recommended.

Extension of the Unified Theory of Acceptance and Use of Technology 2 model for predicting mHealth acceptance using diabetes as an example: a cross-sectional validation study

OBJECTIVES

Mobile health applications are instrumental in the self-management of chronic diseases like diabetes. Technology acceptance models such as Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) have proven essential for predicting the acceptance of information technology. However, earlier research has found that the constructs "perceived disease threat" and "trust" should be added to UTAUT2 in the mHealth acceptance context. This study aims to evaluate the extended UTAUT2 model for predicting mHealth acceptance, represented by behavioral intention, using mobile diabetes applications as an example.

METHODS

We extended UTAUT2 with the additional constructs "perceived disease threat" and "trust". We conducted a web-based survey in German-speaking countries focusing on patients with diabetes and their relatives who have been using mobile diabetes applications for at least 3 months. We analysed 413 completed questionnaires by structural equation modelling.

RESULTS

We could confirm that the newly added constructs "perceived disease threat" and "trust" indeed predict behavioural intention to use mobile diabetes applications. We could also confirm the UTAUT2 constructs "performance expectancy" and "habit" to predict behavioural intention to use mobile diabetes applications. The results show that the extended UTAUT2 model could explain 35.0% of the variance in behavioural intention.

DISCUSSION

Even if UTAUT2 is well established in the information technologies sector to predict technology acceptance, our results reveal that the original UTAUT2 should be extended by "perceived disease threat" and "trust" to better predict mHealth acceptance.

CONCLUSION

Despite the newly added constructs, UTAUT2 can only partially predict mHealth acceptance. Future research should investigate additional mHealth acceptance factors, including how patients perceive trust in mHealth applications.