Encouraging Behavior Changes and Preventing Cardiovascular Diseases Using the Prevent Connect Mobile Health App: Conception and Evaluation of App Quality

Building Bridges between People with Stroke, Families, and Health Professionals: Development of a Blended Care Program for Self-Management

Evidence-informed interventions for stroke self-management support can influence functional capability and social participation. People with stroke should be offered self-management support after hospital discharge. However, in Portugal, there are no known programs of this nature. This study aimed to develop a person-centered and tailored blended care program for post-stroke self-management, taking into account the existing evidence-informed interventions and the perspectives of Portuguese people with stroke, caregivers, and health professionals. An exploratory sequential mixed methods approach was used, including qualitative methods during stakeholder consultation (stage 1) and co-production (stage 2) and quantitative assessment during prototyping (stage 3). After ethical approval, recruitment occurred in three health units. Results from a literature search led to the adaptation of the Bridges Stroke Self-Management Program. In stage one, 47 participants were interviewed, with two themes emerging: (i) Personalized support and (ii) Building Bridges through small steps. In stage two, the ComVida program was developed, combining in-person and digital approaches, supported by a workbook and a mobile app. In stage three, 56 participants evaluated prototypes, demonstrating a strong level of quality. Understandability and actionability of the developed tools obtained high scores (91-100%). The app also showed good usability (A-grade) and high levels of recommendation (5 stars).

User-centered development of an mHealth app for cardiovascular prevention

Background

Mobile health (mHealth) apps can be used for cardiovascular disease (CVD) prevention. User-centered design, evidence-based content and user testing can be applied to ensure a high level of usability and adequate app access.

Objective

To develop and evaluate an mHealth app (HerzFit) for CVD prevention.

Methods

HerzFit´s development included a user-centered design approach and guideline-based content creation based on the identified requirements of the target group. Beta testing and a preliminary usability evaluation of the HerzFit prototype were performed. For evaluation, German versions of the System Usability Scale (SUS) and the mHealth App Usability Questionnaire (GER-MAUQ) as well as free text feedback were applied.

Results

User-centered design thinking led to the definition of four personas. Based on their requirements, HerzFit enables users to individually assess, monitor, and optimize their cardiovascular risk profile. Users are also provided with a variety of evidence-based information on CVD and their risk factors. The user interface and system design followed the identified functional requirements. Beta-testers provided feedback on the structure and functionality and rated the usability of HerzFit´s prototype as slightly above average both in SUS and GER-MAUQ rating. Participants positively noted the variety of functions and information presented in HerzFit, while negative feedback mostly concerned wearable synchronization.

Conclusions

The present study demonstrates the user-centered development of a guideline-based mHealth app for CVD prevention. Beta-testing and a preliminary usability study were used to further improve the HerzFit app until its official release.

Designing personalised mHealth solutions: An overview

INTRODUCTION

Mobile health, or mHealth, is based on mobile information and communication technologies and provides solutions for empowering individuals to participate in healthcare. Personalisation techniques have been used to increase user engagement and adherence to interventions delivered as mHealth solutions. This study aims to explore the current state of personalisation in mHealth, including its current trends and implementation.

MATERIALS AND METHODS

We conducted a review following PRISMA guidelines. Four databases (PubMed, ACM Digital Library, IEEE Xplore, and APA PsycInfo) were searched for studies on mHealth solutions that integrate personalisation. The retrieved papers were assessed for eligibility and useful information regarding integrated personalisation techniques.

RESULTS

Out of the 1,139 retrieved studies, 62 were included in the narrative synthesis. Research interest in the personalisation of mHealth solutions has increased since 2020. mHealth solutions were mainly applied to endocrine, nutritional, and metabolic diseases; mental, behavioural, or neurodevelopmental diseases; or the promotion of healthy lifestyle behaviours. Its main purposes are to support disease self-management and promote healthy lifestyle behaviours. Mobile applications are the most prevalent technological solution. Although several design models, such as user-centred and patient-centred designs, were used, no specific frameworks or models for personalisation were followed. These solutions rely on behaviour change theories, use gamification or motivational messages, and personalise the content rather than functionality. A broad range of data is used for personalisation purposes. There is a lack of studies assessing the efficacy of these solutions; therefore, further evidence is needed.

DISCUSSION

Personalisation in mHealth has not been well researched. Although several techniques have been integrated, the effects of using a combination of personalisation techniques remain unclear. Although personalisation is considered a persuasive strategy, many mHealth solutions do not employ it.

CONCLUSIONS

Open research questions concern guidelines for successful personalisation techniques in mHealth, design frameworks, and comprehensive studies on the effects and interactions among multiple personalisation techniques.

The "Breast-4Y" web app for breast cancer prevention at young age: Development, evaluation, and validation

BACKGROUND

Improving knowledge of risk factors, signs and symptoms positively influence an individual's intention to acquire healthy lifestyle behaviors to prevent breast cancer, to identify breast cancer risk early and seek health advice early. The aim of the present study was to develop and to assess the usability and quality of a web-app (Breast-4Y) designed specifically for younger women to improve their knowledge about breast cancer risk factors and symptoms as well as protective behaviors to reduce their risk.

METHODS

The development of the Breast-4Y web-app, based on Health Belief Model and the Behaviour Change Wheel, comprised four steps: i) analysis of scientific literature regarding breast cancer risk factors, symptoms and preventive lifestyle behaviors; ii) design of web-app; iii) content review by experts; iv) quality and usability assessment by the end-users (n = 20). Web-app usability was evaluated using the Spanish version of the System Usability Scale for the Assessment of Electronic Tools and the quality using the Spanish version of uMARS.

RESULTS

The contents were rated 4.25 or above, indicating high content quality. The mean usability score was 84.9 (SD 12.4), the mean rating for objective quality and subjective quality dimensions mean were 4.2 (SD 0.4) and 3.4 (0.777) respectively, indicating excellent usability and quality. Positive associations (p < .05) were observed between numbers of app used and attitudes to change (r = 0.479), and intention to change (r = 0.539). Strong positive associations (p < .001) were also observed between usability satisfaction and attitudes to change (r = 0.584), intention to change (r = 0.656), and help-seeking (r = 0.656).

CONCLUSIONS

This study provided evidence that Breast-4Y has adequate contents, high quality, and usability. Breast-4Y can be tested in pragmatic trials to assess their effectiveness to reduce the risk of breast cancer, raise women's awareness of breast cancer risk factors, increase women's knowledge of breast cancer symptoms, and adopt protective lifestyle behaviors.

Extending the Privacy Calculus to the mHealth Domain: Survey Study on the Intention to Use mHealth Apps in Germany

BACKGROUND

With the increasing digitalization of the health sector, more and more mobile health (mHealth) apps are coming to the market to continuously collect and process sensitive health data for the benefit of patients and providers. These technologies open up new opportunities to make the health care system more efficient and save costs but also pose potential threats such as loss of data or finances.

OBJECTIVE

This study aims to present an empirical review and adaptation of the extended privacy calculus model to the mHealth domain and to understand what factors influence the intended usage of mHealth technologies.

METHODS

A survey study was conducted to empirically validate our model, using a case vignette as cover story. Data were collected from 250 German participants and analyzed using a covariance-based structural equation model.

RESULTS

The model explains R2=79.3% of the variance in intention to use. The 3 main factors (social norms, attitude to privacy, and perceived control over personal data) influenced the intention to use mHealth apps, albeit partially indirectly. The intention to use mHealth apps is driven by the perceived benefits of the technology, trust in the provider, and social norms. Privacy concerns have no bearing on the intention to use. The attitude to privacy has a large inhibiting effect on perceived benefits, as well as on trust in the provider. Perceived control over personal data clearly dispels privacy concerns and supports the relationship of trust between the user and the provider.

CONCLUSIONS

Based on the privacy calculus, our domain-specific model explains the intention to use mHealth apps better than previous, more general models. The findings allow health care providers to improve their products and to increase usage by targeting specific user groups.

Validating Healthy Eating Index, Glycemic Index, and Glycemic Load with Modern Diets for E-Health Era

Predictors of healthy eating parameters, including the Healthy Eating Index (HEI), Glycemic Index (GI), and Glycemic Load (GL), were examined using various modern diets (n = 131) in preparation for personalized nutrition in the e-health era. Using Nutrition Data Systems for Research computerized software and artificial intelligence machine-learning-based predictive validation analyses, we included domains of HEI, caloric source, and various diets as the potentially modifiable factors. HEI predictors included whole fruits and whole grains, and empty calories. Carbohydrates were the common predictor for both GI and GL, with total fruits and Mexican diets being additional predictors for GI. The median amount of carbohydrates to reach an acceptable GL < 20 was predicted as 33.95 g per meal (median: 3.59 meals daily) with a regression coefficient of 37.33 across all daily diets. Diets with greater carbohydrates and more meals needed to reach acceptable GL < 20 included smoothies, convenient diets, and liquids. Mexican diets were the common predictor for GI and carbohydrates per meal to reach acceptable GL < 20; with smoothies (12.04), high-school (5.75), fast-food (4.48), Korean (4.30), Chinese (3.93), and liquid diets (3.71) presenting a higher median number of meals. These findings could be used to manage diets for various populations in the precision-based e-health era.

Putting undergraduate medical students in AI-CDSS designers' shoes: An innovative teaching method to develop digital health critical thinking

INTRODUCTION

Digital health programs are urgently needed to accelerate the adoption of Artificial Intelligence and Clinical Decision Support Systems (AI-CDSS) in clinical settings. However, such programs are still lacking for undergraduate medical students, and new approaches are required to prepare them for the arrival of new and unknown technologies. At University Paris Cité medical school, we designed an innovative program to develop the digital health critical thinking of undergraduate medical students that consisted of putting medical students in AI-CDSS designers' shoes.

METHODS

We followed the six steps of Kern's approach for curriculum development: identification of needs, definition of objectives, design of an educational strategy, implementation, development of an assessment and design of program evaluation.

RESULTS

A stand-alone and elective AI-CDSS program was implemented for fourth-year medical students. Each session was designed from an AI-CDSS designer viewpoint, with theoretical and practical teaching and brainstorming time on a project that consisted of designing an AI-CDSS in small groups. From 2021 to 2022, 15 students were enrolled: they rated the program 4.4/5, and 80% recommended it. Seventy-four percent considered that they had acquired new skills useful for clinical practice, and 66% felt more confident with technologies. The AI-CDSS program aroused great enthusiasm and strong engagement of students: 8 designed an AI-CDSS and wrote two scientific 5-page articles presented at the Medical Informatics Europe conference; 4 students were involved in a CDSS research project; 2 students asked for a hospital internship in digital health; and 1 decided to pursue PhD training.

DISCUSSION

Putting students in AI-CDSS designers' shoes seemed to be a fruitful and innovative strategy to develop digital health skills and critical thinking toward AI technologies. We expect that such programs could help future doctors work in rapidly evolving digitalized environments and position themselves as key leaders in digital health.

Behavior Change Effectiveness Using Nutrition Apps in People With Chronic Diseases: Scoping Review

BACKGROUND

Cardiovascular disease, cancer, diabetes mellitus, and obesity are common chronic diseases, and their prevalence is reaching an epidemic level worldwide. As the impact of chronic diseases continues to increase, finding strategies to improve care, access to care, and patient empowerment becomes increasingly essential. Health care providers use mobile health (mHealth) to access clinical information, collaborate with care teams, communicate over long distances with patients, and facilitate real-time monitoring and interventions. However, these apps focus on improving general health care concerns, with limited apps focusing on specific chronic diseases and the nutrition involved in the disease state. Hence, available evidence on the effectiveness of mHealth apps toward behavior change to improve chronic disease outcomes is limited.

OBJECTIVE

The objective of this scoping review was to provide an overview of behavior change effectiveness using mHealth nutrition interventions in people with chronic diseases (ie, cardiovascular disease, diabetes mellitus, cancer, and obesity). We further evaluated the behavior change techniques and theories or models used for behavior change, if any.

METHODS

A scoping review was conducted through a systematic literature search in the MEDLINE, EBSCO, PubMed, ScienceDirect, and Scopus databases. Studies were excluded from the review if they did not involve an app or nutrition intervention, were written in a language other than English, were duplicates from other database searches, or were literature reviews. Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines, the systematic review process included 4 steps: identification of records through the database search, screening of duplicate and excluded records, eligibility assessment of full-text records, and final analysis of included records.

RESULTS

In total, 46 studies comprising 256,430 patients were included. There was diversity in the chronic disease state, study design, number of participants, in-app features, behavior change techniques, and behavior models used in the studies. In addition, our review found that less than half (19/46, 41%) of the studies based their nutrition apps on a behavioral theory or its constructs. Of the 46 studies, 11 (24%) measured maintenance of health behavior change, of which 7 (64%) sustained behavior change for approximately 6 to 12 months and 4 (36%) showed a decline in behavior change or discontinued app use.

CONCLUSIONS

The results suggest that mHealth apps involving nutrition can significantly improve health outcomes in people with chronic diseases. Tailoring nutrition apps to specific populations is recommended for effective behavior change and improvement of health outcomes. In addition, some studies (7/46, 15%) showed sustained health behavior change, and some (4/46, 9%) showed a decline in the use of nutrition apps. These results indicate a need for further investigation on the sustainability of the health behavior change effectiveness of disease-specific nutrition apps.

A framework for design and usability testing of telerehabilitation system for adults with chronic diseases: A panoramic scoping review

Objective

This scoping review aimed to identify the design and usability testing of a telerehabilitation (TR) system, and its characteristics and functionalities that are best-suited for rehabilitating adults with chronic diseases.

Methods

Searches were conducted in PubMed, EBSCO, Web of Science, and Cochrane library for studies published between January 2017 and December 2022. We followed the Joanna Briggs Institute guidelines and the framework by Arksey and O'Malley. Screening was undertaken by two reviewers, and data extraction was undertaken by the first author. Then, the data were further reviewed and discussed thoroughly with the team members.

Results

A total of 31 results were identified, with the core criteria of developing and testing a telerehabilitation system, including a mobile app for cardiovascular diseases, cancer, diabetes, and chronic respiratory disorders. All developed systems resulted from multidisciplinary teams and employed mixed-methods research. We proposed the "input-process-output" framework that identified phases of both system design and usability testing. Through system design, we reported the use of user-centered design, iterative design, users' needs and characteristics, theory underpinning development, and the expert panel in 64%, 75%, 86%, 82%, and 71% of the studies, respectively. We recorded the application of moderated usability testing, unmoderated testing (1), and unmoderated testing (2) in 74%, 63%, and 15% of the studies, respectively. The identified design and testing activities produced a matured system, a high-fidelity prototype, and a released system in 81.5%, 15%, and 3.5%, respectively.

Conclusion

This review provides a framework for TR system design and testing for a wide range of chronic diseases that require prolonged management through remote monitoring using a mobile app. The identified "input-process-output" framework highlights the inputs, design, development, and improvement as components of the system design. It also identifies the "moderated-unmoderated" model for conducting usability testing. This review illustrates characteristics and functionalities of the TR systems and healthcare professional roles.

Monitoring Risk Factors and Improving Adherence to Therapy in Patients With Chronic Kidney Disease (Smit-CKD Project): Pilot Observational Study

BACKGROUND

Chronic kidney disease is a major public health issue, with about 13% of the general adult population and 30% of the elderly affected. Patients in the last stage of this disease have an almost uniquely high risk of death and cardiovascular events, with reduced adherence to therapy representing an additional risk factor for cardiovascular morbidity and mortality. Considering the increased penetration of mobile phones, a mobile app could educate patients to autonomously monitor cardiorenal risk factors.

OBJECTIVE

With this background in mind, we developed an integrated system of a server and app with the aim of improving self-monitoring of cardiovascular and renal risk factors and adherence to therapy.

METHODS

The software infrastructure for both the Smit-CKD server and Smit-CKD app was developed using standard web-oriented development methodologies preferring open source tools when available. To make the Smit-CKD app suitable for Android and iOS, platforms that allow the development of a multiplatform app starting from a single source code were used. The integrated system was field tested with the help of 22 participants. User satisfaction and adherence to therapy were measured by questionnaires specifically designed for this study; regular use of the app was measured using the daily reports available on the platform.

RESULTS

The Smit-CKD app allows the monitoring of cardiorenal risk factors, such as blood pressure, weight, and blood glucose. Collected data are transmitted in real time to the referring general practitioner. In addition, special reminders improve adherence to the medication regimen. Via the Smit-CKD server, general practitioners can monitor the clinical status of their patients and their adherence to therapy. During the test phase, 73% (16/22) of subjects entered all the required data regularly and sent feedback on drug intake. After 6 months of use, the percentage of regular intake of medications rose from 64% (14/22) to 82% (18/22). Analysis of the evaluation questionnaires showed that both the app and server components were well accepted by the users.

CONCLUSIONS

Our study demonstrated that a simple mobile app, created to self-monitor modifiable cardiorenal risk factors and adherence to therapy, is well tolerated by patients affected by chronic kidney disease. Further studies are required to clarify if the use of this integrated system will have long-term effects on therapy adherence and if self-monitoring of risk factors will improve clinical outcomes in this population.

Football Fandom as a Platform for Digital Health Promotion and Behaviour Change: A Mobile App Case Study

Background: The last decade has seen a dramatic shift toward the study of fitness surveillance, thanks in part to the emergence of mobile health (mHealth) apps that allow users to track their health through a variety of data-driven insights. This study examines the adoption trends and community mediation of the mobile fitness application ‘FanFit’, a platform aimed at promoting physical activity among sports fans by creating a fitness app branded to their favourite team for health promotion. Objective: Our study looked at the impact of a specially designed mobile app (FanFit) as a digital health intervention for initiating and maintaining physical activity as part of football club membership. Our analysis indicates that app users will adopt healthier behaviours as a result of the app’s sense of fan community and behaviour change. Methods: The findings reported here are based on an implementation of the FanFit app and, in particular, on those who participated in a more in-depth study (n = 30). These participants were Rangers FC supporters with a mix of genders (n = 19 males and n = 11 females). Focus groups and interviews were conducted with participants to ascertain users’ perspectives on the most effective methods for nudging users toward adopting and maintaining a pattern of fitness behaviours. Results: The findings show that the user community was interested in fitness and wanted to live a ‘healthy lifestyle,’ which was augmented and fuelled by the app’s competitive architecture design. Furthermore, the data reveal a new fan-health discourse about a person’s developing wants, talents, and identities as embodied beings. Conclusions: We have developed and presented valid links between the use of sports club apps and health programmes. The app could be useful for sports programmes and club providers looking for mHealth applications that provide community support through fan discourse with opportunities for both male and female fans.