Implementation science to expand an mHealth intervention for improving retention in care for women living with HIV and their children

Thesis (Ph.D.)--University of Washington, 2016-08

mHealth in Urology: A Review of Experts' Involvement in App Development

Smartphones are increasingly playing a role in healthcare and previous studies assessing medical applications (apps) have raised concerns about lack of expert involvement and low content accuracy. However, there are no such studies in Urology. We reviewed Urology apps with the aim of assessing the level of participation of healthcare professionals (HCP) and scientific Urology associations in their development.

A development and evaluation process for mHealth interventions: examples from New Zealand

The authors established a process for the development and testing of mobile phone-based health interventions that has been implemented in several mHealth interventions developed in New Zealand. This process involves a series of steps: conceptualization, formative research to inform the development, pretesting content, pilot study, pragmatic randomized controlled trial, and further qualitative research to inform improvement or implementation. Several themes underlie the entire process, including the integrity of the underlying behavior change theory, allowing for improvements on the basis of participant feedback, and a focus on implementation from the start. The strengths of this process are the involvement of the target audience in the development stages and the use of rigorous research methods to determine effectiveness. The limitations include the time required and potentially a less formalized and randomized approach than some other processes. This article aims to describe the steps and themes in the mHealth development process, using the examples of a mobile phone video messaging smoking cessation intervention and a mobile phone multimedia messaging depression prevention intervention, to stimulate discussion on these and other potential methods.

A mHealth cardiac rehabilitation exercise intervention: findings from content development studies

BACKGROUND: Involving stakeholders and consumers throughout the content and study design ensures interventions are engaging and relevant for end-users. The aim of this paper is to present the content development process for a mHealth (mobile phone and internet-based) cardiac rehabilitation (CR) exercise intervention.

METHODS: An innovative mHealth intervention was developed with patient input using the following steps: conceptualization, formative research, pre-testing, and pilot testing. Conceptualization, including theoretical and technical aspects, was undertaken by experts. For the formative component, focus groups and interviews with cardiac patients were conducted to discuss their perceptions of a mHealth CR program. A general inductive thematic approach identified common themes. A preliminary library of text and video messages were then developed. Participants were recruited from CR education sessions to pre-test and provide feedback on the content using an online survey. Common responses were extracted and compiled. An iterative process was used to refine content prior to pilot testing and conduct of a randomized controlled trial.

RESULTS: 38 CR patients and 3 CR nurses participated in the formative research and 20 CR patients participated in the content pre-testing. Participants perceived the mHealth program as an effective approach to inform and motivate patients to exercise. For the qualitative study, 100% (n = 41) of participants thought it to be a good idea, and 11% of participants felt it might not be useful for them, but would be for others. Of the 20 participants who completed the online survey, 17 out of 20 (85%) stated they would sign up to a program where they could receive information by video messages on a website, and 12 out of 20 (60%) showed interest in a texting program. Some older CR patients viewed technology as a potential barrier as they were unfamiliar with text messaging or did not have mobile phones. Steps to instruct participants to receive texts and view the website were written into the study protocol. Suggestions to improve videos and wording of texts were fed back to the content development team and refined.

CONCLUSIONS: Most participants thought a mHealth exercise program was an effective way to deliver exercise-based CR. The results were used to develop an innovative multimedia exercise intervention. A randomized controlled trial is currently underway.

mHealth Multidisciplinary Verticals

An in-depth overview of the emerging concept; Mobile Health (mHealth), mHealth Multidisciplinary Verticals links applications and technologies to key market and vendor players. It highlights interdependencies and synergies between various stakeholders which drive the research forces behind mHealth. The book explores the trends and directions where this vertical market is headed.

LTE networking : extending the reach for sensors in mHealth applications

Sensor and electronic-health networks are widely utilized at home and in industry/research applications. In a local sense, a sensor-to-sensor network can have a range of a few meters to a couple of hundred meters (ZigBee Pro can extend this range up to 2000 m). With the deployment of mobile technology in the healthcare space (mobile-Health ‘m-Health’) and using cellular coverage, the range can virtually be unbounded. However, supporting bounded delay (end-to-end delay), class of service, and quality of service for critical sensor-mHealth applications may become challenging. This challenge can be alarmingly extended when thousands of users run their sensor-mHealth applications simultaneously and depend on limited coverage of the cell tower to transmit their health-related data across. In this paper we will discuss how the 3rd Generation Partnership Project–Long Term Evolution networks can address such aggregation issues, and discuss the challenges and provide recommendations.

Privacy-enabled mobile-health (mhealth)-based diabetic solution

Diabetes is one of the leading chronic diseases affecting the lives of millions globally and early detection and treatment of this disease can serve to improve the quality of life for patients as well as suspend further health complications arising from diabetes. Continuous Glucose Monitors (CGM) and Insulin Pumps (IP) have been widely deployed to monitor the sugar levels in the blood stream and inject appropriate amounts of insulin to compensate for the underperforming pancreas functions of the patients’ bodies and thereby may provide appropriate treatment solutions for many diabetic sufferers. With the invention and deployment of Smartphones, the quality and performance associated with treating diabetes has reached new heights, however the privacy and security of mobilebased diabetic systems remain in ongoing challenges. This paper aims to focus on the privacy and security challenges of Mobile-Health (mHealth)-based Diabetic solutions.

Mobile health (mHealth) biomedical imaging paradigm

Technology assisted methods for medical diagnosis and biomedical health monitoring are rapidly shifting from classical invasive methods to handheld-based non-invasive approaches. Biomedical imagining is one of the most prominent practices of non-invasive mechanisms in medical applications. This paper considers the medical imaging schemes for Mobile Health (mHealth) applications and studies the feasibility of future mobile systems for accommodating image informatics capabilities.

mHealth technologies to influence physical activity and sedentary behaviors: behavior change techniques, systematic review and meta-analysis of randomized controlled trials

BACKGROUND: mHealth programs offer potential for practical and cost-effective delivery of interventions capable of reaching many individuals.

PURPOSE: To (1) compare the effectiveness of mHealth interventions to promote physical activity (PA) and reduce sedentary behavior (SB) in free-living young people and adults with a comparator exposed to usual care/minimal intervention; (2) determine whether, and to what extent, such interventions affect PA and SB levels and (3) use the taxonomy of behavior change techniques (BCTs) to describe intervention characteristics.

METHODS: A systematic review and meta-analysis following PRISMA guidelines was undertaken to identify randomized controlled trials (RCTs) comparing mHealth interventions with usual or minimal care among individuals free from conditions that could limit PA. Total PA, moderate-to-vigorous intensity physical activity (MVPA), walking and SB outcomes were extracted. Intervention content was independently coded following the 93-item taxonomy of BCTs.

RESULTS: Twenty-one RCTs (1701 participants-700 with objectively measured PA) met eligibility criteria. SB decreased more following mHealth interventions than after usual care (standardised mean difference (SMD) -0.26, 95 % confidence interval (CI) -0.53 to -0.00). Summary effects across studies were small to moderate and non-significant for total PA (SMD 0.14, 95 % CI -0.12 to 0.41); MVPA (SMD 0.37, 95 % CI -0.03 to 0.77); and walking (SMD 0.14, 95 % CI -0.01 to 0.29). BCTs were employed more frequently in intervention (mean = 6.9, range 2 to 12) than in comparator conditions (mean = 3.1, range 0 to 10). Of all BCTs, only 31 were employed in intervention conditions.

CONCLUSIONS: Current mHealth interventions have small effects on PA/SB. Technological advancements will enable more comprehensive, interactive and responsive intervention delivery. Future mHealth PA studies should ensure that all the active ingredients of the intervention are reported in sufficient detail.

Remotely delivered exercise-based cardiac rehabilitation: design and content development of a novel mHealth platform

BACKGROUND: Participation in traditional center-based cardiac rehabilitation exercise programs (exCR) is limited by accessibility barriers. Mobile health (mHealth) technologies can overcome these barriers while preserving critical attributes of center-based exCR monitoring and coaching, but these opportunities have not yet been capitalized on.

OBJECTIVE: We aimed to design and develop an evidence- and theory-based mHealth platform for remote delivery of exCR to any geographical location.

METHODS: An iterative process was used to design and develop an evidence- and theory-based mHealth platform (REMOTE-CR) that provides real-time remote exercise monitoring and coaching, behavior change education, and social support.

RESULTS: The REMOTE-CR platform comprises a commercially available smartphone and wearable sensor, custom smartphone and Web-based applications (apps), and a custom middleware. The platform allows exCR specialists to monitor patients' exercise and provide individualized coaching in real-time, from almost any location, and provide behavior change education and social support. Intervention content incorporates Social Cognitive Theory, Self-determination Theory, and a taxonomy of behavior change techniques. Exercise components are based on guidelines for clinical exercise prescription.

CONCLUSIONS: The REMOTE-CR platform extends the capabilities of previous telehealth exCR platforms and narrows the gap between existing center- and home-based exCR services. REMOTE-CR can complement center-based exCR by providing an alternative option for patients whose needs are not being met. Remotely monitored exCR may be more cost-effective than establishing additional center-based programs. The effectiveness and acceptability of REMOTE-CR are now being evaluated in a noninferiority randomized controlled trial.

Iterative development of MobileMums : a physical activity intervention for women with young children.

Background To describe the iterative development process and final version of ‘MobileMums’: a physical activity intervention for women with young children (<5 years) delivered primarily via mobile telephone (mHealth) short messaging service (SMS). Methods MobileMums development followed the five steps outlined in the mHealth development and evaluation framework: 1) conceptualization (critique of literature and theory); 2) formative research (focus groups, n= 48); 3) pre-testing (qualitative pilot of intervention components, n= 12); 4) pilot testing (pilot RCT, n= 88); and, 5) qualitative evaluation of the refined intervention (n= 6). Results Key findings identified throughout the development process that shaped the MobileMums program were the need for: behaviour change techniques to be grounded in Social Cognitive Theory; tailored SMS content; two-way SMS interaction; rapport between SMS sender and recipient; an automated software platform to generate and send SMS; and, flexibility in location of a face-to-face delivered component. Conclusions The final version of MobileMums is flexible and adaptive to individual participant’s physical activity goals, expectations and environment. MobileMums is being evaluated in a community-based randomised controlled efficacy trial (ACTRN12611000481976).

Consumers' behavioural responses toward technology-based social products

This thesis examined the determinants of consumers’ use of emerging mental health services delivered via mobile phone technology, which promise to provide cost-effective psychotherapeutic support where and when needed. It builds on the Model of Goal-Directed Behaviour by recognising the role that competition between behavioural alternatives plays in influencing consumers’ decision to use these services. The research employed a three-study, mixed-methodological approach.

Consumer engagement with eHealth information through smartphones and tablets : an Australian perspective

This paper is a work in progress that examines current consumer engagement with eHealth information through Smartphones or tablets. We focus on three activity types: seeking, posting and ‘other’ engagement activity and compare two age groups, 25-40s and over 40-55s. Findings show that around 30% of the younger age group is engaging with Government and other Health providers’ websites, receiving eHealth emails, and reading other people’s comments about health related issues in online discussion groups/websites/blog. Approximately 20% engage with Government and other Health providers’ social media and watch or listen to audio or video podcasts. For the older age group, their most active engagement with eHealth information is in the seeking category through Government or other health websites (approximately 15%), and less than 10% for social media sites. Their posting activity is less than 5%. Other activities show that less than 15% of the older age group engages through receiving emails and reading blogs, less than 10% watch or listen to podcasts, and their online consulting activity is less than 7%. We note that scores are low for both groups in terms of engaging with eHealth information through Twitter.

The Mobile Application Rating Scale (MARS): A new tool to measure the quality of health mobile applications

Smartphone technology provides free or inexpensive access to mental health and wellbeing resources. As a result the use of mobile applications for these purposes has increased significantly in recent years. Yet, there is currently no app quality assessment alternative to the popular ‘star’-ratings, which are often unreliable. This presentation describes the development of the Mobile Application Rating Scale (MARS) a new measure for classifying and rating the quality of mobile applications. A review of existing literature on app and web quality identified 25 published papers, conference proceedings, and online resources (published since 1999), which identified 372 explicit quality criteria. Qualitative analysis identified five broad categories of app quality rating criteria: engagement, functionality, aesthetics, information quality, and overall satisfaction, which were refined into the 23-item MARS. Independent ratings of 50 randomly selected mental health and wellbeing mobile apps indicated the MARS had excellent levels of internal consistency (α = 0.92) and inter-rater reliability (ICC = 0.85). The MARS provides practitioners and researchers with an easy-to-use, simple, objective and reliable tool for assessing mobile app quality. It also provides mHealth professionals with a checklist for the design and development of high quality apps.