Empowering Patients Through Digital Technologies

Mobile health initiatives aim to give patients more medical information and to empower them over their medical treatments. However, information overload and lack of digital literacy may hinder patient empowerment. This chapter investigates opportunities and challenges of patient empowerment and mobile health. The authors analyze the different definitions used in the literature to characterize patient empowerment and mobile health, discussing implications for all the care actors involved. Although the adoption rate of mobile technologies is at its infant stage and challenges still outweigh the benefits of patient empowerment, mobile health apps can foster the progress towards patient-centered care.

A Review of the Quality and Impact of Mobile Health Apps

Mobile health applications (apps) have transformed the possibilities for health promotion and disease self-management; however, their promise is not fully realized owing to their reliance on commercial ecosystems for development and distribution. This review provides an overview of the types of mobile health apps and describes key stakeholders in terms of how apps are used, developed, and regulated. I outline key challenges facing consumers, public health professionals, and policy makers in evaluating the quality of health apps and summarize what is known about the impact of apps on health outcomes and health equity. I suggest that factors within the wider mobile ecosystem largely define the impact of health apps and, most notably, practices around the collection and commercialization of user data. Finally, I suggest that upstream public health strategies, grounded in an understanding of corporate influences on health, are necessary to promote healthy digital environments in which mobile health app innovation can flourish. Expected final online publication date for the Annual Review of Public Health, Volume 43 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Associations between Behaviour Change Techniques and engagement with mobile health apps: Systematic review protocol (Preprint)

BACKGROUND The use of digitally-enabled care and the emphasis on self-management of health is growing. Mobile health apps provide a promising means of supporting health behaviour change; however, engagement with them is often poor and evidence of their impact on health outcomes is lacking. As engagement is a key prerequisite to health behaviour change, it is essential to understand how engagement with mobile health apps and their target health behaviours can be better supported. Despite an increasing recognition of the importance of engagement in the literature, there is still a lack of understanding of how different components of engagement are associated with specific techniques that aim to change behaviours. OBJECTIVE The purpose of this systematic review protocol is to provide a synthesis of the associations between various Behaviour Change Techniques (BCTs)and the different components of engagement (and their outcome measures) with mobile health apps. METHODS The review protocol was structured using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) and the Population, Intervention, Comparator, and Outcome (PICO) frameworks. Six databases will be systematically searched: PubMed, Embase, Cumulative Index to Nursing and Allied Health Literature (CINAHL), APA PsycInfo, ScienceDirect, and Web of Science. Title and abstract screening, full-text review, and data extraction will be conducted by two independent reviewers. Data will be extracted into a predetermined form, and any disagreements in screening or data extraction will be discussed, with a third reviewer consulted if consensus cannot be reached. Risk of bias will be assessed using the Cochrane Collaboration Risk of Bias 2 and ROBINS-I tools and descriptive and thematic analyses will be used to summarise the relationships between BCTs and the different components of engagement. RESULTS The systematic review has not been started. It is expected to be completed and submitted for publication by January 2022. CONCLUSIONS This systematic review will summarize the associations between different BCTs and various components and measures of engagement with mobile health apps. This will identify areas where further research is needed to examine BCTs that could potentially support effective engagement and help to inform the design and evaluation of future mobile health apps. CLINICALTRIAL PROSPERO (reference number TBD)

Challenges in Participant Engagement and Retention using Mobile Health Apps: A Literature Review (Preprint)

BACKGROUND Mobile health (mHealth) apps are revolutionizing the way clinicians and researchers monitor and manage the health of their participants. However, many studies using mHealth apps are hampered by substantial participant drop-out, or attrition, which may impact the representativeness of the sample and the effectiveness of the study. It is therefore imperative for researchers to understand what makes the participants stay with mHealth apps and/or studies using mHealth apps. OBJECTIVE This study aimed to review current peer-reviewed research literature in order to identify notable factors and strategies used in participant engagement and retention of adults. METHODS We conducted a systematic search of PubMed, MedLine, and PsycINFO databases for mHealth studies that evaluated and assessed issues and/or strategies to improve engagement and retention of adults from 2015 to 2020. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Notable themes were identified and narratively compared amongst different studies. A binomial regression model was generated to examine factors affecting retention. RESULTS Of the 389 identified studies, 62 were included in the review. Overall, the majority of studies were at least partially successful in maintaining participant engagement throughout. Factors related to particular elements of the app (e.g., feedback, appropriate reminders, and in-app support from peers or coaches) and strategies for research (e.g., compensation and niche samples) that promote retention were identified. Factors that obstruct retention were also identified (e.g., lack of support features, technical difficulties, and usefulness of app). The regression model results showed that a participant is more likely to not be retained than they would be retained. CONCLUSIONS Retaining participants is an omnipresent challenge for mHealth studies. The insights from this review should help inform future studies about factors and strategies to improve participant retention.

Phenotyping Adopters of Mobile Applications Among Patients With COPD: A Cross-Sectional Study

Effectiveness of technology-based interventions to improve physical activity (PA) in people with COPD is controversial. Mixed results may be due to participants' characteristics influencing their use of and engagement with mobile health apps. This study compared demographic, clinical, physical and PA characteristics of patients with COPD using and not using mobile apps in daily life. Patients with COPD who used smartphones were asked about their sociodemographic and clinic characteristics, PA habits and use of mobile apps (general and PA-related). Participants performed a six-minute walk test (6MWT), gait speed test and wore an accelerometer for 7 days. Data were compared between participants using (App Users) and not using (Non-App Users) mobile apps. A sub-analysis was conducted comparing characteristics of PA–App Users and Non-Users. 59 participants were enrolled (73% Male; 66.3 ± 8.3 yrs; FEV1 48.7 ± 18.4% predicted): 59% were App Users and 25% were PA-App Users. Significant differences between App Users and Non-App Users were found for age (64.2 ± 8.9 vs. 69.2 ± 6.3yrs), 6MWT (462.9 ± 91.7 vs. 414.9 ± 82.3 m), Gait Speed (Median 1.5 [Q1–Q3: 1.4–1.8] vs. 2.0 [1.0–1.5]m/s), Time in Vigorous PA (0.6 [0.2–2.8] vs. 0.14 [0.1–0.7]min) and Self-Reported PA (4.0 [1.0–4.0] vs. 1.0 [0.0–4.0] Points). Differences between PA–App Users and Non-Users were found in time in sedentary behavior (764.1 [641.8–819.8] vs. 672.2 [581.2–749.4] min) and self-reported PA (4.0 [2.0–6.0] vs. 2.0 [0.0–4.0] points). People with COPD using mobile apps were younger and had higher physical capacity than their peers not using mobile apps. PA-App Users spent more time in sedentary behaviors than Non-Users although self-reporting more time in PA.

Heuristic Evaluation of a Top-Rated Diabetes Self-Management App

Objective The purpose of this study was to evaluate the usability of a top-rated diabetes app. Such apps are intended to markedly support the achievement of optimal health and financial outcomes by providing patients with substantive and continual support for self-management of their disease between periodic clinician visits. Poor usability can deter use which is especially concerning in patients with diabetes due to prevalence of the disease and impact of self-management on long-term prognosis. Methods A diabetes app was selected due to the prevalence and seriousness of the disease. A heuristic evaluation was then performed to collect and analyze data on the usability of the app based on Nielsen's heuristics. Pareto analysis was used to illustrate the contribution of each type of heuristic violation, augmented by a stacked bar chart illuminating associated severity. Results There were 51 heuristic violations on the opening screen, violating 6 of Nielsen's 10 heuristics. Pareto analysis revealed 29 (57%) of the heuristic violations involved a match between system and real world and 8 (16%) aesthetic and minimalist design. Severity ratings ranged from 1.0 to 4.0 (mean: 3.01) with 80% comprising a major usability problem and 6% a usability catastrophe. Conclusion Studies show that people with diabetes are more likely to receive greater benefit from a diabetes app if they are easy to use. The number and severity of heuristic violations in this study suggest that the commercialization of mobile health apps may play a factor in bypassing experts in clinical informatics during the design phase of development. Usability and associated benefits received from mobile health apps can be enhanced by debugging the user interface of identified heuristic violations during design. Waiting to correct ongoing usability issues while apps are in production can result in patients disengaging from use of digital health tools engendering poorer outcomes.

The App Rating Inventory: A Novel Method for Evaluating Mobile Apps (Preprint)

BACKGROUND A prodigious number of mobile health apps have flooded the market. The lack of guidelines for identifying high-quality apps from the overwhelming number of available apps creates confusion forestalling clinical adoption. OBJECTIVE The Defense Health Agency’s (DHA) Connected Health Branch developed the app rating inventory (ARI), an objective rating system with capability for broad application across condition areas. METHODS During the development of the ARI, three rounds of testing were conducted to enhance the tool’s performance, reduce redundancy, validate the ARI’s broad application, and assess potential subjectivity. RESULTS The ARI is a 28-item, three-criterion tool. The evidence criterion contains six items, and the content and customizability criterion each contain eleven items. Scoring is based on a simple binary system: either the app contains the feature or it does not. The 28 items are weighted equally; no one item is considered more (or less) important than any other. Each rated app receives four scores: a score for evidence, content, and customizability, and a total score (the sum of the three categories.). Higher scores indicate that the app obtained a positive score on more items than a similar app with a lower score. The evidence, content and customizability scores allow a clinician to make focused decisions when selecting an app for clinical use. CONCLUSIONS Using a two-phased process (market research followed by ratings), the ARI is able to evaluate apps for evidence, content and customizability. Scoring systems provide guidance; they filter down hundreds of apps in a disease category to a handful for consideration. Indeed, apps are not new medicine; in many cases, they are a novel delivery system for proven interventions.