mHealth System Research Articles

An Adaptive Mobile Health System to Support Self-Management for Persons With Chronic Conditions and Disabilities: Usability and Feasibility Studies.

BackgroundPersons with chronic conditions and disabilities (PwCCDs) are vulnerable to secondary complications. Many of these secondary complications are preventable with proactive self-management and proper support. To enhance PwCCDs' self-management skills and conveniently receive desired support, we have developed a mobile health (mHealth) system called iMHere. In 2 previous clinical trials, iMHere was successfully used to improve health outcomes of adult participants with spina bifida and spinal cord injury. To further expand use of iMHere among people with various types of disabilities and chronic diseases, the system needs to be more adaptive to address 3 unique challenges: 1) PwCCDs have very diverse needs with regards to self-management support, 2) PwCCDs’ self-management needs may change over time, and 3) it is a challenge to keep PwCCDs engaged and interested in long-term self-management.ObjectiveThe aim of this study was to develop an adaptive mHealth system capable of supporting long-term self-management and adapting to the various needs and conditions of PwCCDs.MethodsA scalable and adaptive architecture was designed and implemented for the new version, iMHere 2.0. In this scalable architecture, a set of mobile app modules was created to provide various types of self-management support to PwCCDs with the ability to add more as needed. The adaptive architecture empowers PwCCDs with personally relevant app modules and allows clinicians to adapt these modules in response to PwCCDs’ evolving needs and conditions over time. Persuasive technologies, social support, and personalization features were integrated into iMHere 2.0 to engage and motivate PwCCDs and support long-term usage. Two initial studies were performed to evaluate the usability and feasibility of the iMHere 2.0 system.ResultsThe iMHere 2.0 system consists of cross-platform client and caregiver apps, a Web-based clinician portal, and a secure 2-way communication protocol for providing interactions among these 3 front-end components, all supported by a back-end server. The client and caregiver apps have 12 adaptive app modules to support various types of self-management tasks. The adaptive architecture makes it possible for PwCCDs to receive personalized app modules relevant to their conditions with or without support from various types of caregivers. The personalization and persuasive technologies in the architecture can be used to engage PwCCDs for long-term usage of the iMHere 2.0 system. Participants of the usability study were satisfied with the iMHere 2.0 client app. The feasibility evaluation revealed several practical issues to consider when implementing the system on a large scale.ConclusionsWe developed an adaptive mHealth system as a novel method to support diverse needs in self-management for PwCCDs that can dynamically change over time. The usability of the client app is high, and it was feasible for PwCCDs to use in supporting personalized and evolving self-care needs.

Evaluation of an innovative mobile health programme for the self-management of chronic obstructive pulmonary disease (MH-COPD): protocol of a randomised controlled trial

IntroductionChronic obstructive pulmonary disease (COPD) is the fourth leading cause of death globally. In outpatient care, the self-management of COPD is essential, but patient adherence to this remains suboptimal. The...

Edge computing in multi-scope service-oriented mobile healthcare systems

IoT based e-Health solutions is an upcoming trend which will revolutionize the healthcare in the near future. IoT has evolved from micro-electro-mechanical systems (MEMS), wireless technologies and Internet which together offer connectivity of systems, microelectronic devices, and medical services and allow data processing at the edge. That at the same time allows to save computational resources and avoid unnecessary point of failure, such as centralized synchronization point. Monitoring of patients’ vital signs parameters (measured at home) is achieved by using modern Internet of Things technology which provides networkable connections between portable diagnostic sensors, their cell phones, cloud data storage with patients’ Personal Health Records and professional health providers. This paper explores possibilities of using fog computing approach to shift data processing and computations from cloud to the edge and to build a multi-scope infrastructure for mHealth and citizen-observation system, based on SOA approach.

Understanding Determinants of Health Care Professionals' Perspectives on Mobile Health Continuance and Performance.

BackgroundWith the widespread use of mobile technologies, mobile information systems have become crucial tools in health care operations. Although the appropriate use of mobile health (mHealth) may result in major advances in expanding health care coverage (increasing decision-making speeds, managing chronic conditions, and providing suitable health care in emergencies), previous studies have argued that current mHealth research does not adequately evaluate mHealth interventions, and it does not provide sufficient evidence regarding the effects on health.ObjectiveThe aim of this study was to facilitate the widespread use of mHealth systems; an accurate evaluation of the systems from the users’ perspective is essential after the implementation and use of the system in daily health care practices. This study extends the expectation-confirmation model by using characteristics of individuals, technology, and tasks to identify critical factors affecting mHealth continuance and performance from the perspective of health care professionals (HCPs).MethodsA questionnaire survey was used to collect data from HCPs who were experienced in using mHealth systems of a Taiwanese teaching hospital. In total, 282 questionnaires were distributed, and 201 complete and valid questionnaires were returned, thus indicating a valid response rate of 71.3% (201/282). The collected data were analyzed using WarpPLS version 5.0 (ScriptWarp Systems).ResultsThe results revealed that mHealth continuance (R2=0.522) was mainly affected by perceived usefulness, technology maturity, individual habits, task mobility, and user satisfaction, whereas individual performance (R2=0.492) was affected by mHealth continuance. In addition, user satisfaction (R2=0.548) was affected by confirmation and perceived usefulness of mHealth, whereas perceived usefulness (R2=0.521) was affected by confirmation. This implied that confirmation played a key role in affecting perceived usefulness and user satisfaction. Furthermore, the results showed that mHealth continuance positively affected individual performance.ConclusionsThe identified critical factors influencing mHealth continuance and performance can be used as a useful assessment tool by hospitals that have implemented mHealth systems to facilitate the use and infusion of the systems. Furthermore, the results can help health care institutions that intend to introduce or develop mHealth applications to identify critical issues and effectively allocate limited resources to mHealth systems.

Employing a user-centered cognitive walkthrough to evaluate a mHealth diabetes self-management application: A case study and beginning method validation.

Self-management of chronic diseases using mobile health (mHealth) systems and applications is becoming common. Current evaluation methods such as formal usability testing can be very costly and time-consuming; others may be more efficient but lack a user focus. We propose an enhanced cognitive walkthrough (CW) method, the user-centered CW (UC-CW), to address identified deficiencies in the original technique and perform a beginning validation with think aloud protocol (TA) to assess its effectiveness, efficiency and user acceptance in a case study with diabetes patient users on a mHealth self-management application. A total of 12 diabetes patients at University of Utah Health, USA, were divided into UC-CW and think aloud (TA) groups. The UC-CW method included: making the user the main evaluator for detecting usability problems, having a dual domain facilitator, and using three other improved processes: validated task development, higher level tasks and a streamlined evaluation process. Users interacted with the same mHealth application for both methods. Post-evaluation assessments included the NASA RTLX instrument and a set of brief interview questions. Participants had similar demographic characteristics. A total of 26 usability problems were identified with the UC-CW and 20 with TA. Both methods produced similar ratings: severity across all views (UC-CW = 2.7 and TA = 2.6), numbers of problems in the same views (Main View [UC-CW = 11, TA = 10], Carbohydrate Entry View [UC-CW = 4, TA = 3] and List View [UC-CW = 3, TA = 3]) with similar heuristic violations (Match Between the System and Real World [UC-CW = 19, TA = 16], Consistency and Standards [UC-CW = 17, TA = 15], and Recognition Rather than Recall [UC-CW = 13, TA = 10]). Both methods converged on eight usability problems, but the UC-CW group detected five critical issues while the TA group identified two. The UC-CW group identified needed personalized features for patients' disease needs not identified with TA. UC-CW was more efficient on average time per identified usability problem and on the total evaluation process with patients. NASA RTLX scores indicated that participants experienced the UC-CW half as cognitively demanding. Common themes from interviews indicated the UC-CW as enjoyable and easy to perform while TA was considered somewhat awkward and more cognitively challenging. UC-CW was effective for finding severe, recurring usability problems and it highlighted the need for personalized user features. The method was also efficient and had high user acceptance. These results indicate UC-CW's utility and user acceptance in evaluating a mHealth self-management application. It provides an additional usability evaluation technique for researchers.

The Impact of the mKidney mHealth System on Live Donor Follow-Up Compliance: Protocol for a Randomized Controlled Trial.

BackgroundEvery year, more than 5500 healthy people in the United States donate a kidney for the medical benefit of another person. The Organ Procurement and Transplantation Network (OPTN) requires transplant hospitals to monitor living kidney donors (LKDs) for 2 years postdonation. However, the majority (115/202, 57%) of transplant hospitals in the United States continue to fail to meet nationally mandated requirements for LKD follow-up. A novel method for collecting LKD follow-up is needed to ease both the transplant hospital-level and patient-level burden. We built mKidney—a mobile health (mHealth) system designed specifically to facilitate the collection and reporting of OPTN-required LKD follow-up data. The mKidney mobile app was developed on the basis of input elicited from LKDs, transplant providers, and thought leaders.ObjectiveThe primary objective of this study is to evaluate the impact of the mKidney smartphone app on LKD follow-up rates.MethodsWe will conduct a two-arm randomized controlled trial (RCT) with LKDs who undergo LKD transplantation at Methodist Specialty and Transplant Hospital in San Antonio, Texas. Eligible participants will be recruited in-person by a study team member at their 1-week postdonation clinical visit and randomly assigned to the intervention or control arm (1:1). Participants in the intervention arm will receive the mHealth intervention (mKidney), and participants in the control arm will receive the current standard of follow-up care. Our primary outcome will be policy-defined complete (all components addressed) and timely (60 days before or after the expected visit date) submission of LKD follow-up data at required 6-month, 1-year, and 2-year visits. Our secondary outcome will be hospital-level compliance with OPTN reporting requirements at each visit. Data analysis will follow the intention-to-treat principle. Additionally, we will collect quantitative and qualitative process data regarding the implementation of the mKidney system.ResultsWe began recruitment for this RCT in May 2018. We plan to enroll 400 LKDs over 2 years and follow participants for the 2-year mandated follow-up period.ConclusionsThis pilot RCT will evaluate the impact of the mKidney system on rates of LKD and hospital compliance with OPTN-mandated LKD follow-up at a large LKD transplant hospital. It will provide valuable information on strategies for implementing such a system in a clinical setting and inform effect sizes for future RCT sample size calculations.International Registered Report Identifier (IRRID)DERR1-10.2196/11000

An mHealth App for Users with Dexterity Impairments: Accessibility Study.

BackgroundA mobile health (mHealth) system called iMHere (interactive mobile health and rehabilitation) was developed to support individuals with chronic conditions and disability in their self-management regimens. The initial design of iMHere, however, lacked sufficient accessibility for users with a myriad of dexterity impairments. The accessibility of self-management apps is essential in ensuring usability.ObjectiveThis study aims to increase the usability of the iMHere system for users with dexterity impairments by increasing the app’s accessibility.MethodsWe targeted the accessibility redesign by focusing on the physical presentation and the navigability of the iMHere apps. Six participants presenting with dexterity impairments were included in the usability study of the original and redesigned apps.ResultsWe observed a lower number of touches needed to complete tasks (P=.09) and time to complete individual tasks (P=.06) with the redesigned app than with the original app; a significantly lower time for users to complete all tasks (P=.006); and a significantly lower error rate (P=.01) with the redesigned app than with the original app. In fact, no errors occurred with use of the redesigned app. Participant-reported overall average usability of the redesigned app (P=.007) and usability of individual modules (P<.001) were significantly higher than that of the original app due mostly to better ease of use and learnability, interface quality, and reliability.ConclusionsImproved usability was achieved using a redesigned app. This study offers insight into the importance of personalization in enhancing the accessibility and also identifies strategies for improving usability in app development.

Mobile Phone-Based Telemedicine Practice in Older Chinese Patients with Type 2 Diabetes Mellitus: Randomized Controlled Trial.

BackgroundPrevious studies on telemedicine interventions have shown that older diabetic patients experience difficulty in using computers, which is a barrier to remote communication between medical teams and older diabetic patients. However, older people in China tend to find it easy to use mobile phones and personal messaging apps that have a user-friendly interface. Therefore, we designed a mobile health (mHealth) system for older people with diabetes that is based on mobile phones, has a streamlined operation interface, and incorporates maximum automation.ObjectiveThe goal of the research was to investigate the use of mobile phone–based telemedicine apps for management of older Chinese patients with type 2 diabetes mellitus (T2DM). Variables of interest included efficacy and safety.MethodsA total of 91 older (aged over 65 years) patients with T2DM who presented to our department were randomly assigned to one of two groups. Patients in the intervention group (n=44) were provided glucometers capable of data transmission and received advice pertaining to medication, diet, and exercise via the mHealth telemedicine system. Patients assigned to the control group (n=47) received routine outpatient care with no additional intervention. Patients in both groups were followed up at regular 3-month intervals.ResultsAfter 3 months, patients in the intervention group showed significant (P<.05) improvement in postprandial plasma glucose level. After 6 months, patients in the intervention group exhibited a decreasing trend in postprandial plasma glucose and glycated hemoglobin levels compared with the baseline and those in the control group (P<.05).ConclusionsMobile phone–based telemedicine apps help improve glycemic control in older Chinese patients with T2DM.Trial RegistrationChina Clinical Trial Registration Center ChiCTR 1800015214; http://www.chictr.org.cn/showprojen.aspx?proj=25949 (Archived by WebCite at http://www.webcitation.org/73wKj1GMq).

Exploring the Design of mHealth Systems for Health Behavior Change using Mobile Biosensors

A person’s health behavior plays a vital role in mitigating their risk of disease and promoting positive health outcomes. In recent years, mHealth systems have emerged to offer novel approaches for encouraging and supporting users in changing their health behavior. Mobile biosensors represent a promising technology in this regard; that is, sensors that collect physiological data (e.g., heart rate, respiration, skin conductance) that individuals wear, carry, or access during their normal daily activities. mHealth system designers have started to use the health information from physiological data to deliver behavior-change interventions. However, little research provides guidance about how one can design mHealth systems to use mobile biosensors for health behavior change. In order to address this research gap, we conducted an exploratory study. Following a hybrid approach that combines deductive and inductive reasoning, we integrated a body of fragmented literature and conducted 30 semi-structured interviews with mHealth stakeholders. From this study, we developed a theoretical framework and six general design guidelines that shed light on the theoretical pathways for how the mHealth interface can facilitate behavior change and provide practical design considerations.

User-Centric Networks Selection With Adaptive Data Compression for Smart Health

The increasing demand for intelligent and sustainable healthcare services has prompted the development of smart health systems. Rapid advances in wireless access technologies and in-network data reduction techniques can significantly assist in implementing such smart systems through providing seamless integration of heterogeneous wireless networks, medical devices, and ubiquitous access to data. Utilization of the spectrum across diverse radio technologies is expected to significantly enhance network capacity and quality of service (QoS) for emerging applications such as remote monitoring over mobile-health (m-health) systems. However, this imposes an essential need to develop innovative networks selection mechanisms that account for energy efficiency while meeting application quality requirements. In this context, this paper proposes an efficient networks selection mechanism with adaptive compression for improving medical data delivery over heterogeneous m-health systems. We consider different performance aspects, as well as networks characteristics and application requirements, so as to obtain an efficient solution that grasps the conflicting nature of the various users’ objectives and addresses their inherent tradeoffs. The proposed methodology advocates a user-centric approach towards leveraging heterogeneous wireless networks to enhance the performance of m-health systems. Simulation results show that our solution significantly outperforms state-of-the-art techniques.

Promoting access equity and improving health care for women, children and people living with HIV/AIDS in Burkina Faso through mHealth.

ABSTRACTBackgroundIn Burkina Faso, access to health services for women, children and people living with HIV/AIDS (PLWHAs) remains limited. Mobile telephony offers an alternative solution for reaching these individuals. The objective of the study was to improve equity of access to health care and information among women and PLWHAs by reinforcing community participation.MethodsUsing a quasi-experimental approach, a mobile telephone system was set up at five health centres to provide an automated reminder service for health care consultation appointments. Performance evaluations based on key performance indicators were subsequently conducted.ResultsA total of 1501 pregnant women and 301 PLWHAs were registered and received appointment reminders. A 7.34% increase in prenatal coverage, an 84% decrease in loss to follow-up for HIV (P < 0.001) and a 31% increase in assisted deliveries in 2016 (P < 0.0001) were observed in intervention areas. However, there was no statistically significant difference between intervention site and control site (P= 0.451 > 0.05) at post-intervention. Efforts to involve community members in decision-making processes contributed to improved health system governance.ConclusionMhealth may improve maternal and child health and the health of PLWHAs. However, establishment of a mHealth system requires taking into account community dynamics and potential technological challenges.Keywordsaccess to care, Burkina Faso, equity, health system governance, mobile telephony, Nouna

Tilt Tracker: Technical Note on an mHealth System to Monitor and Prevent Ulcer Development Among Power Wheelchair Users

Tilt Tracker: Technical Note on an mHealth System to Monitor and Prevent Ulcer Development Among Power Wheelchair Users

Designing mHealth for maternity services in primary health facilities in a low-income setting \u2013 lessons from a partially successful implementation

BackgroundIncreasing mobile phone ownership, functionality and access to mobile-broad band internet services has triggered growing interest to harness the potential of mobile phone technology to improve health services in low-income settings. The present project aimed at designing an mHealth system that assists midlevel health workers to provide better maternal health care services by automating the data collection and decision-making process. This paper describes the development process and technical aspects of the system considered critical for possible replication. It also highlights key lessons learned and challenges during implementation.MethodsThe mHealth system had front-end and back-end components. The front-end component was implemented as a mobile based application while the back-end component was implemented as a web-based application that ran on a central server for data aggregation and report generation. The current mHealth system had four applications; namely, data collection/reporting, electronic health records, decision support, and provider education along the continuum of care including antenatal, delivery and postnatal care. The system was pilot-tested and deployed in selected health centers of North Shewa Zone, Amhara region, Ethiopia.ResultsThe system was used in 5 health centers since Jan 2014 and later expanded to additional 10 health centers in June 2016 with a total of 5927 electronic forms submitted to the back-end system. The submissions through the mHealth system were slightly lower compared to the actual number of clients who visited those facilities as verified by record reviews. Regarding timeliness, only 11% of the electronic forms were submitted on the day of the client visit, while an additional 17% of the forms were submitted within 10 days of clients’ visit. On average forms were submitted 39 days after the day of clients visit with a range of 0 to 150 days.ConclusionsIn conclusion, the study illustrated that an effective mHealth intervention can be developed using an open source platform and local resources. The system impacted key health outcomes and contributed to timely and complete data submission. Lessons learned through the process including success factors and challenges are discussed.

Effectiveness of an mHealth-Based Electronic Decision Support System for Integrated Management of Chronic Conditions in Primary Care: The mWellcare Cluster-Randomized Controlled Trial.

The burden of noncommunicable diseases and their risk factors has rapidly increased worldwide, including in India. Innovative management strategies with electronic decision support and task sharing have been assessed for hypertension, diabetes mellitus, and depression individually, but an integrated package for multiple chronic condition management in primary care has not been evaluated. In a prospective, multicenter, open-label, cluster-randomized controlled trial involving 40 community health centers, using hypertension and diabetes mellitus as entry points, we evaluated the effectiveness of mWellcare, an mHealth system consisting of electronic health record storage and an electronic decision support for the integrated management of 5 chronic conditions (hypertension, diabetes mellitus, current tobacco and alcohol use, and depression) versus enhanced usual care among patients with hypertension and diabetes mellitus in India. At trial end (12-month follow-up), using intention-to-treat analysis, we examined the mean difference between arms in change in systolic blood pressure and glycated hemoglobin as primary outcomes and fasting blood glucose, total cholesterol, predicted 10-year risk of cardiovascular disease, depression score, and proportions reporting tobacco and alcohol use as secondary outcomes. Mixed-effects regression models were used to account for clustering and other confounding variables. Among 3698 enrolled participants across 40 clusters (mean age, 55.1 years; SD, 11 years; 55.2% men), 3324 completed the trial. There was no evidence of difference between the 2 arms for systolic blood pressure (Δ=-0.98; 95% CI, -4.64 to 2.67) and glycated hemoglobin (Δ=0.11; 95% CI, -0.24 to 0.45) even after adjustment of several key variables (adjusted differences for systolic blood pressure: - 0.31 [95% CI, -3.91 to 3.29]; for glycated hemoglobin: 0.08 [95% CI, -0.27 to 0.44]). The mean within-group changes in systolic blood pressure in mWellcare and enhanced usual care were -13.65 mm Hg versus -12.66 mm Hg, respectively, and for glycated hemoglobin were -0.48% and -0.58%, respectively. Similarly, there were no differences in the changes between the 2 groups for tobacco and alcohol use or other secondary outcomes. We did not find an incremental benefit of mWellcare over enhanced usual care in the management of the chronic conditions studied. URL: https://www. gov. Unique identifier: NCT02480062.

Developing mobile health applications for neglected tropical disease research.

Mobile applications (apps) can bring health research and its potential downstream benefits closer to underserved populations. Drawing on experience developing an app for detecting and referring cases of cutaneous leishmaniasis in Colombia, called Guaral/app, we review key steps in creating such mobile health (mHealth) tools. These require consideration of the sociotechnical context using methods such as systems analysis and human-centered design (HCD), predicated on engagement and iteration with all stakeholders. We emphasize usability and technical concerns and describe the interdependency of technical and human considerations for mHealth systems in rural communities.

Assessing the Attitudes and Perceptions Regarding the Use of Mobile Health Technologies for Living Kidney Donor Follow-Up: Survey Study.

BackgroundIn 2013, the Organ Procurement and Transplantation Network began requiring transplant centers in the United States to collect and report postdonation living kidney donor follow-up data at 6 months, 1 year, and 2 years. Despite this requirement, <50% of transplant centers have been able to collect and report the required data. Previous work identified a number of barriers to living kidney donor follow-up, including logistical and administrative barriers for transplant centers and cost and functional barriers for donors. Novel smartphone-based mobile health (mHealth) technologies might reduce the burden of living kidney donor follow-up for centers and donors. However, the attitudes and perceptions toward the incorporation of mHealth into postdonation care among living kidney donors are unknown. Understanding donor attitudes and perceptions will be vital to the creation of a patient-oriented mHealth system to improve living donor follow-up in the United States.ObjectiveThe goal of this study was to assess living kidney donor attitudes and perceptions associated with the use of mHealth for follow-up.MethodsWe developed and administered a cross-sectional 14-question survey to 100 living kidney donors at our transplant center. All participants were part of an ongoing longitudinal study of long-term outcomes in living kidney donors. The survey included questions on smartphone use, current health maintenance behaviors, accessibility to health information, and attitudes toward using mHealth for living kidney donor follow-up.ResultsOf the 100 participants surveyed, 94 owned a smartphone (35 Android, 58 iPhone, 1 Blackberry), 37 had accessed their electronic medical record on their smartphone, and 38 had tracked their exercise and physical activity on their smartphone. While 77% (72/93) of participants who owned a smartphone and had asked a medical question in the last year placed the most trust with their doctors, nurses, or other health care professionals regarding answering a health-related question, 52% (48/93) most often accessed health information elsewhere. Overall, 79% (74/94) of smartphone-owning participants perceived accessing living kidney donor information and resources on their smartphone as useful. Additionally, 80% (75/94) perceived completing some living kidney donor follow-up via mHealth as useful. There were no significant differences in median age (60 vs 59 years; P=.65), median years since donation (10 vs 12 years; P=.45), gender (36/75, 36%, vs 37/75, 37%, male; P=.57), or race (70/75, 93%, vs 18/19, 95%, white; P=.34) between those who perceived mHealth as useful for living kidney donor follow-up and those who did not, respectively.ConclusionsOverall, smartphone ownership was high (94/100, 94.0%), and 79% (74/94) of surveyed smartphone-owning donors felt that it would be useful to complete their required follow-up with an mHealth tool, with no significant differences by age, sex, or race. These results suggest that patients would benefit from an mHealth tool to perform living donor follow-up.

An Evolutionary Game-Theoretic Approach for Assessing Privacy Protection in mHealth Systems.

With the rapid deployment of mobile technologies and their applications in the healthcare domain, privacy concerns have emerged as one of the most critical issues. Traditional technical and organizational approaches used to address privacy issues ignore economic factors, which are increasingly important in the investment strategy of those responsible for ensuring privacy protection. Taking the mHealth system as the context, this article builds an evolutionary game to model three types of entities (including system providers, hospitals and governments) under the conditions of incomplete information and bounded rationality. Given that the various participating entities are often unable to accurately estimate their own profits or costs, we propose a quantified approach to analyzing the optimal strategy of privacy investment and regulation. Numerical examples are provided for illustration and simulation purpose. Based upon these examples, several countermeasures and suggestions for privacy protection are proposed. Our analytical results show that governmental regulation and auditing has a significant impact on the strategic choice of the other two entities involved. In addition, the strategic choices of system providers and hospitals are not only correlated with profits and investment costs, but they are also significantly affected by free riding. If the profit growth coefficients increase to a critical level, mHealth system providers and hospitals will invest in privacy protection even without the imposition of regulations. However, the critical level is dependent on the values of the parameters (variables) in each case of investment and profits.

An acceptance testing approach for Internet of Things systems

Internet of things (IoT) systems are becoming ubiquitous and assuring their quality is fundamental. Unfortunately, a few proposals for testing these complex, and often safety-critical, systems are present in the literature. The authors propose an approach for acceptance testing of IoT systems adopting graphical user interfaces as a principal way of interaction. Acceptance testing is a type of black box testing based on test scenarios, i.e. sequences of steps/actions performed by the user or the system. In their approach, test scenarios are derived from a state machine that expresses the behaviour of the system under test, and test cases are derived from them by specifying the actual data and assertions and made executable by implementing the corresponding test scripts. As a case study, they selected a mobile health IoT system for diabetes management composed of local sensors/actuators, smartphones, and a remote cloud-based system. The effectiveness of the approach has been evaluated by measuring the capability of two test suites implemented using different localisation strategies (visual and structure-based) in detecting mutants of the original m-health system. Results show the effectiveness of the test suites implemented by following the proposed approach since 93% of the generated mutants have been detected.

Using mHealth to Deliver a Home-Based Testing and Counseling Program to Improve Linkage to Care and ART Adherence in Rural South Africa.

Community-based HIV testing and counseling (HTC) programs have become an important part of the healthcare system in South Africa and other low- and middle-income countries with a high HIV prevalence and strained primary healthcare system. Current HTC programs excel at identifying people living with HIV (PLH) but leave gaps in linkage to care and antiretroviral therapy (ART) as most HTC programs do not have the capacity to ensure that linkage has occurred. This article presents the protocol for an mHealth study, that is, pilot testing a mobile platform in KwaZulu-Natal (KZN), South Africa, to improve linkage to care and ART adherence after home-based HTC. Testing data are shared with designated clinics. PLH are identified using fingerprint scans, mobile numbers, or South African IDs. If PLH do not present at a designated clinic after testing HIV positive, study field staff are sent SMS alerts to prompt follow-up visits. Similarly, if PLH do not refill ART prescriptions after their initial 1-month dose runs out, SMS alerts that are sent to field staff. This paper presents the mHealth study protocol and baseline sample characteristics (N = 101 PLH). Analyses will summarize rates of linkage to care and ART prescription refills. Cost-effectiveness analyses will examine the costs and benefits of linkage and ART adherence using our mHealth system. Linkage to care rates will be compared between our study and a historical control, that is, provided by a prior HTC program that was conducted in KZN without our mHealth system (n = 615).

A Personal Decision Support System for Heart Failure Management (HeartMan): study protocol of the HeartMan randomized controlled trial

BackgroundHeart failure (HF) is a highly prevalent chronic disease, for which there is no cure available. Therefore, improving disease management is crucial, with mobile health (mHealth) being a promising technology. The aim of the HeartMan study is to evaluate the effect of a personal mHealth system on top of standard care on disease management and health-related quality of life (HRQoL) in HF.MethodsHeartMan is a randomized controlled 1:2 (control:intervention) proof-of-concept trial, which will enrol 120 stable ambulatory HF patients with reduced ejection fraction across two European countries. Participants in the intervention group are equipped with a multi-monitoring health platform with the HeartMan wristband sensor as the main component. HeartMan provides guidance through a decision support system on four domains of disease management (exercise, nutrition, medication adherence and mental support), adapted to the patient’s medical and psychological profile. The primary endpoint of the study is improvement in self-care and HRQoL after a six-months intervention. Secondary endpoints are the effects of HeartMan on: behavioural outcomes, illness perception, clinical outcomes and mental state.DiscussionHeartMan is technologically the most innovative HF self-management support system to date. This trial will provide evidence whether modern mHealth technology, when used to its full extent, can improve HRQoL in HF.Trial registrationThis trial has been registered on https://clinicaltrials.gov/ct2/show/NCT03497871, on April 13 2018 with registration number NCT03497871.