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Introduction Home-based programmes for cardiac rehabilitation play a key role in the recovery of patients with coronary artery disease. However, their necessary educational and motivational components have been rarely implemented with the help of modern mobile technologies. We developed a mobile health system designed for motivating patients to adhere to their rehabilitation programme by providing exercise monitoring, guidance, motivational feedback, and educational content. Methods Our multi-disciplinary approach is based on mapping "desired behaviours" into specific system's specifications, borrowing concepts from Fogg's Persuasive Systems Design principles. A randomised controlled trial was conducted to compare mobile-based rehabilitation (55 patients) versus standard care (63 patients). Results Some technical issues related to connectivity, usability and exercise sessions interrupted by safety algorithms affected the trial. For those who completed the rehabilitation (19 of 55), results show high levels of both user acceptance and perceived usefulness. Adherence in terms of started exercise sessions was high, but not in terms of total time of performed exercise or drop-outs. Educational level about heart-related health improved more in the intervention group than the control. Exercise habits at 6 months follow-up also improved, although without statistical significance. Discussion Results indicate that the adopted design methodology is promising for creating applications that help improve education and foster better exercise habits, but further studies would be needed to confirm these indications. [ABSTRACT FROM AUTHOR]

Background Despite their potential for improving health outcomes, mobile-based home monitoring systems for heart failure have not yet been taken up widely by the patients and providers. Objectives To design and iteratively move towards a personalised mobile health monitoring system for patients living with heart failure, according to their health care and usability needs. Methods We present an iterative approach to refining a remote health monitoring system that is based on interactions between different actors (patients, clinicians, social scientists and engineers) and supports the collection of quantitative and qualitative information about user experience and engagement. Patients were provided with tablet computers and commercially available sensing devices (a blood pressure monitor, a set of weighing scales, and a pulse oximeter) in order to complete physiological measurements at home, answer symptom-specific questionnaires, review their personal readings, view educational material on heart failure self-management, and communicate with their health professionals. The system supported unobtrusive remote software upgrades via an application distribution channel and the activation or deactivation of functional components by health professionals during run-time operation. We report early findings from the application of this approach in a cohort of 26 heart failure patients (mean age 72 ± 15 years), their caregivers and healthcare professionals who participated in the SUPPORT-HF (Seamless User-centred Proactive Provision Of Risk-stratified Treatment for Heart Failure) study over a one-year study period (mean patient follow-up duration = 270 ± 62 days). Results The approach employed in this study led to several system upgrades dealing in particular with patient requirements for better communication with the development team and personalised self-monitoring interfaces. Engagement with the system was constantly high throughout the study and during the last week of the evaluation, 23 patients (88%) used the system at least once and 16 patients (62%) at least three times. Conclusions Designers of future mobile-based home monitoring systems for heart failure and other chronic conditions could leverage the described approach as a means of meeting patients’ needs during system use within the home environment and facilitating successful uptake. [ABSTRACT FROM AUTHOR]

Background: A vast amount of mobile apps have been developed during the past few months in an attempt to "flatten the curve" of the increasing number of COVID-19 cases.Objective: This systematic review aims to shed light into studies found in the scientific literature that have used and evaluated mobile apps for the prevention, management, treatment, or follow-up of COVID-19.Methods: We searched the bibliographic databases Global Literature on Coronavirus Disease, PubMed, and Scopus to identify papers focusing on mobile apps for COVID-19 that show evidence of their real-life use and have been developed involving clinical professionals in their design or validation.Results: Mobile apps have been implemented for training, information sharing, risk assessment, self-management of symptoms, contact tracing, home monitoring, and decision making, rapidly offering effective and usable tools for managing the COVID-19 pandemic.Conclusions: Mobile apps are considered to be a valuable tool for citizens, health professionals, and decision makers in facing critical challenges imposed by the pandemic, such as reducing the burden on hospitals, providing access to credible information, tracking the symptoms and mental health of individuals, and discovering new predictors. [ABSTRACT FROM AUTHOR]

Background: Mobile health (mHealth) technology has the potential to play a key role in improving the health of patients with chronic non-communicable diseases.Objectives: We present a review of systematic reviews of mHealth in chronic disease management, by showing the features and outcomes of mHealth interventions, along with associated challenges in this rapidly growing field.Methods: We searched the bibliographic databases of PubMed, Scopus, and Cochrane to identify systematic reviews of mHealth interventions with advanced technical capabilities (e.g., Internet-linked apps, interoperation with sensors, communication with clinical platforms, etc.) utilized in randomized clinical trials. The original studies included the reviews were synthesized according to their intervention features, the targeted diseases, the primary outcome, the number of participants and their average age, as well as the total follow-up duration.Results: We identified 5 reviews respecting our inclusion and exclusion criteria, which examined 30 mHealth interventions. The highest percentage of the interventions targeted patients with diabetes (n = 19, 63%), followed by patients with psychotic disorders (n = 7, 23%), lung diseases (n = 3, 10%), and cardiovascular disease (n = 1, 3%). 14 studies showed effective results: 9 in diabetes management, 2 in lung function, and 3 in mental health. Significantly positive outcomes were reported in 8 interventions (n = 8, 47%) from 17 studies assessing glucose concentration, one intervention assessing physical activity, 2 interventions (n = 2, 67%) from 3 studies assessing lung function parameters, and 3 mental health interventions assessing N-back performance, medication adherence, and number of hospitalizations. Divergent features were adopted in 14 interventions with significantly positive outcomes, such as personalized goal setting (n = 10, 71%), motivational feedback (n = 5, 36%), and alerts for health professionals (n = 3, 21%). The most significant found challenges in the development and evaluation of mHealth interventions include the design of studies with high quality, the construction of robust interventions in combination with health professional inputs, and the identification of tools and methods to improve patient adherence.Conclusions: This review found mixed evidence regarding the health benefits of mHealth interventions for patients living with chronic diseases. Further rigorous studies are needed to assess the outcomes of personalized mHealth interventions toward the optimal management of chronic diseases. [ABSTRACT FROM AUTHOR]