We conducted a parallel randomized controlled trial to assess feasibility as previously described [14] at 2 medical centers—Vanderbilt University Medical Center and the Ohio State University—from 2018 to 2022 (Checklist 1). Inclusion criteria encompassed patients within the SCD clinic with the following genotypes (Hemoglobin SS, Hemoglobin SC, and Hemoglobin Sβ-thal): proficient in spoken and written English, possessing a smartphone or computer, and being 18 to 70 years old. The trial ended due to reaching recruitment goals.

Participants were divided into two arms: (1) the mHealth app arm, where individuals received the mHealth app along with a booklet containing patient-facing guidelines, and (2) the booklet-only arm, where participants received solely a booklet with patient-facing guidelines. Participants were randomized in 1:1 ratio between the 2 arms without any restrictions. Randomization allocation sequence was determined by using a computer-generated random allocation sequence and implemented using the Research Electronic Data Capture (REDCap) randomization module.

The study involved an initial baseline and follow-up visits at 6 months. During the initial visit, after consenting, participants were randomized, and baseline surveys were administered by key study personnel. Participants in the mHealth app arm were introduced to the mHealth app, which took approximately 10‐15 minutes. At the 6-month follow-up, surveys were repeated, and all survey instruments were available electronically through REDCap, administered via iPads.

Institutional review boards at both centers—Vanderbilt University Medical Center (171036) and the Ohio State University (2020H0468)—approved the trial. Recruitment occurred at SCD clinics, and written informed consent was obtained before randomization. Compensation included a US $25 gift card for the initial visit and US $50 for the 6-month follow-up. Data were anonymized for analysis to help preserve privacy and confidentiality (Multimedia Appendices 1-4).

The mHealth app comprised 2 main components: a web application featuring patient-facing guideline content and a REDCap project. The web application mirrored the content found in the previously mentioned booklets. It included sections providing guideline-based information on treatments (such as medications, transfusions, and transplants), complications (including acute sickle cell pain, infections, acute chest syndrome, pulmonary hypertension, leg ulcers, strokes, kidney disease, and depression), and wellness topics (women’s health, prevention and screening, pain triggers avoidance, stress management, dental care, diet and exercise, as well as tobacco, alcohol, and drug use).

The REDCap project featured a profile and interactive functionalities. Initially, participants could answer questions to generate their profiles, allowing them to access links for reviewing guidelines, editing their profiles, tracking pain, setting goals or missions, taking chapter quizzes related to the guidelines, and creating either a pain or an asthma action plan. The REDCap project also facilitated sending daily text messages at a time of the participant’s choosing, containing a customizable message and a link to their profile.

Missions were user-defined missions, goals, or tasks to complete during the trial. Specifically, participants could set a 6-month mission and as many weekly missions as they would like. Some examples of these missions included: “To better manage my pain without pain meds,” “Drink more water,” “No hospital visits,” “To Take all my medication on time each day,” “Recover from the hospital,” “To get a 9 to 5 job,” “Lose weight,” and “Establish and commit to a night routine to relax.”

Participants could document their daily pain experiences within the pain tracker and the strategies used to manage pain, including recording their mood. The goals feature enabled participants to monitor their weekly or 6-month goals. Chapter quizzes were available to reinforce the website’s content and the guidelines. The pain action plan guided individuals through a stepwise approach to managing acute pain at home. In contrast, the asthma action plan was designed for those seeking to develop a strategy for managing their asthma in collaboration with their health care provider. This mHealth app aimed to reinforce key guideline points and promote patient engagement through quizzes and text message reminders.

Primary and secondary outcomes were previously described [14]; in this manuscript, we evaluated mHealth app feature usage and associations with our outcomes. Pain diaries, goal-setting diaries, and quizzes were REDCap surveys, so we measured app feature usage based on the completion of these REDCap surveys. SCD knowledge outcome was measured with a 40-item questionnaire survey covering the guidelines during baseline and follow-up visits. Demographics were self-reported through surveys. Hospitalizations and acute health care utilization (hospitalization, emergency room visits, and day-hospital visits) outcomes were determined by chart review in the first 6 months following baseline and within 6 months prebaseline.

The sample for analysis of app usage was those who were randomized to the mHealth app arm, completed all baseline surveys, and either completed the study up to but not necessarily including the final endpoint survey or withdrew for a reason possibly related to the intervention (ie, not transplant or death). We used descriptive statistics, including median and IQR for continuous data and percentages for categorical data. Linear and generalized linear models evaluated baseline variables and usage differences between groups. Associations between usage of app components (diaries, quizzes, missions, and pain action plan) were evaluated using Wilcoxon test and Spearman correlations, as appropriate.

A total of 67 participants were randomly allocated; 37 were enrolled in the mHealth app arm and 30 in the booklet alone arm (Figure 3). In total, 30 users who completed baseline surveys and were introduced to the mHealth app were eligible for app usage analysis: 26 completed the entire study, 3 withdrew after completing all baseline surveys but before the final follow-up survey, and 1 did not complete the final follow-up survey. There were no harms or unintended effects. Table 1 shows the baseline characteristics of the participants. All eligible users created a profile and filled out at least one pain diary. While there were no requirements to use the mHealth app, 90% (27/30) participants used at least one additional feature. Features in order of highest usage were missions (26/30, 87% of eligible participants), additional pain diaries (13/30, 43%), quizzes (8/30, 27%), and pain action plans (6/30, 20%). Further, 50% (15/30) participants used multiple features, not including the first pain diary (Table 2).

mHealth apps are a potentially scalable, efficient, and sustainable strategy to improve adult care in SCD. However, there is a knowledge gap regarding patterns of the usage of multipurpose apps in rare diseases, such as SCD. Our study is the first to demonstrate that adults with SCD have different usage patterns of a multipurpose mHealth app for self-management, and certain features may be related to improved patient outcomes. Almost all users used multiple features. Highly engaged participants were more likely to use either quizzes or diaries, but not both. We also saw that completing certain features, such as missions, was associated with lower hospitalizations, although not significant. Complex chronic diseases, such as SCD, could benefit from multipurpose apps that allow users to engage based on preferences and needs.

As this study was not focused on one part of our app, engagement with features in this mHealth app was entirely patient-driven and may demonstrate the expected real-world use of an mHealth app in this population. Users were most engaged with missions but least engaged with action plans. Missions were one of the most straightforward, least time-consuming features that users could fill out independently, whereas action plans require more time and typically would be done with the provider. Interestingly, less than half of the participants used the pain diaries, potentially because they were not the primary function of the mHealth app or trial. This finding contradicts other studies that demonstrated the high use of pain diaries in SCD [8,15,16]. Usage of pain diaries in the general SCD population could be lower when it is not the primary goal of an mHealth app as part of a specific research study. Further study is needed into why some users completed pain diaries, among other mHealth app features, while others did not. While there were associations between the use of one feature of the mHealth app and another, participants tended to engage with some but not all features. For example, highly engaged participants engaged with either quizzes or diaries, but not both. Pain action plans, pain diaries, quizzes, and missions were all associated with each other. Almost all participants who engaged with one feature besides the missions would typically engage with additional features.

User engagement with mHealth apps is a critical area of study, as it directly influences the effectiveness of these interventions in promoting treatment adherence and self-management among individuals with chronic health conditions. Recent reviews have described challenges in engagement with mHealth apps, including (1) inconsistent terminology and measurements, limiting our ability to compare results across studies, complicating the development of effective engagement strategies [17]; (2) usability issues, where complex interfaces and poor user experiences in mHealth apps can deter individuals with chronic diseases from consistent use [18]; (3) data privacy and security concerns that can deter users from engaging with mHealth apps [19]; and (4) a lack of personalization, where generic content does not cater to individual user needs can lead to reduced engagement [20]. While our mHealth app included user-centered design to overcome usability issues and tailor the intervention to this population’s specific needs, is within REDCap, which has enhanced data privacy and security, and has personalization features, including text message reminders and individualized plans, the app’s current version had limited functionality to measure engagement robustly. By addressing these barriers and implementing the suggested strategies, developers and healthcare providers can improve user engagement with mHealth applications, leading to better health outcomes. Future research on user engagement could include post-study user interviews or focus groups to obtain more detailed information about why users engaged with certain functionality and not others.

A notable but not statistically significant relationship was observed between missions completed and hospitalizations. Findings from other studies demonstrated improved outcomes associated with apps [21]. However, while many studies show improvements in outcomes like asthma or diabetes control, few have demonstrated improvements in outcomes like hospitalizations. Also, others have shown the opposite effect of increased hospitalization rates with mHealth app usage [22,23]. Also, in adults with SCD, no studies demonstrated improvement in hospitalizations or acute health care utilization using mHealth apps. However, the feasibility study of our app showed a nonstatistically significant improvement in outcomes. A larger trial with more participants is the next logical step that could demonstrate which of the mHealth app’s features might improve outcomes.

Baseline knowledge and female gender identity were associated with more feature usage, whereas other variables, such as age, did not show any significant differences. Others have demonstrated that demographics, such as age, are associated with different usage [24] of an mHealth app; however, only female gender identity was associated with one more feature use. Classifying different types of users may be necessary for understanding and improving long-term engagement.

Our study had a low attrition rate; however, sustained engagement varied. Other studies have demonstrated a wide range of attrition rates from 9% to 82% and an average of 43% [25]. Our attrition rate was lower, which could be because our mHealth app used strategies that have led to lower attrition in other studies, including multitouch interventions and tailored messaging [25]. However, another reason for the low attrition could have been because our mHealth app had multiple features that allowed users to engage in the most important features to them and their disease For sustained engagement with the app, we observed that 70% of the users completed more functions after enrollment, with a continued decline throughout the study period, with only a few participants completing functions after trial completion. However, these features were not the primary feature of the trial, but we could not assess all app usage due to the app’s limited analytics. Future research with better analytics and a longer follow-up period is needed in understanding sustained usage of this mHealth app.

Since this mHealth app was built primarily in REDCap, the mHealth app can be accessed and used by any of the REDCap Consortium 7178 active partners across 156 countries. Providing a framework for an mHealth app built within REDCap using base features and external modules would demonstrate scalability by allowing researchers in the REDCap Consortium to efficiently adapt the mHealth app to develop, test, and confirm ideal configurations and settings for user engagement and data collection, which impact data quality and quantity and overall significance and applicability of study results. The consortium can download this mHealth app REDCap project and tailor it to their needs and local/national guidelines. Also, the solution would be more sustainable as it would not require maintenance and updates when operating systems change, like native Apple and Android apps, as the institutions typically update their versions of REDCap. However, for those outside of the REDCap consortium, there would be limitations on adapting this app quickly for their purposes, which would limit scalability to that app for nonconsortium partners.

Several limitations occurred in our study. First, the sample size was small, so we could not observe significant associations between mHealth app feature usage and outcomes. A larger randomized controlled trial would allow for further evaluation of the effects of important app features on outcomes. Second, we could not evaluate the interaction between participants and the guidelines feature of the mHealth app. While we measured how to access guidelines and other app features, we could not measure guideline review. This limited functionality also precluded us from being able to measure app usage after participants completed the trial. Our next version of the mHealth app will include analytics to evaluate guideline use. Third, the app’s current version did not include the ability to assess usage in terms of time, so we could not evaluate how long it took to perform different functions. Future hybrid effectiveness-implementation studies with better analytical functionality, a larger population, longer follow-up, and an implementation framework could help our understanding of improving outcomes, understanding user engagement, including sustained use after the trial is completed, and implementing this mHealth app.. Finally, this study did not assess other determinants of app usage (eg, participation in a community-based organization) or other healthcare experiences (eg, discrimination).

Results of our first-ever multipurpose mHealth app for adults with SCD demonstrated that (1) participants will use an mHealth app and use certain features of an mHealth app depending on their needs, even if these features were not the primary purpose of the mHealth app, and (2) that certain features may lead to improvement in outcomes. A multipurpose mHealth app can help engage participants in features they want to use and potentially increase and improve outcomes. This trial’s results have important implications for improving the health of a patient population facing significant healthcare and health information technology disparities.