Dataset Information

Real-World Evidence of User Engagement With Mobile Health for Diabetes Management: Longitudinal Observational Study.

ABSTRACT:

Background

Patient support apps have risen in popularity and provide novel opportunities for self-management of diabetes. Such apps offer patients to play an active role in monitoring their condition, thereby increasing their own treatment responsibility. Although many health apps require active user engagement to be effective, there is little evidence exploring engagement with mobile health (mHealth).

Objective

This study aims to analyze the extent to which users engage with mHealth for diabetes and identify patient characteristics that are associated with engagement.

Methods

The analysis is based on real-world data obtained by Novo Nordisk's Cornerstones4Care Powered by Glooko diabetes support app. User engagement was assessed as the number of active days and using measures expressing the persistence, longevity, and regularity of interaction within the first 180 days of use. Beta regressions were estimated to assess the associations between user characteristics and engagement outcomes for each module of the app.

Results

A total of 9051 individuals initiated use after registration and could be observed for 180 days. Among these, 55.39% (5013/9051) used the app for one specific purpose. The average user activity ratio varied from 0.05 (medication and food) to 0.55 (continuous glucose monitoring), depending on the module of the app. Average user engagement was lower if modules required manual data entries, although the initial uptake was higher for these modules. Regression analyses further revealed that although more women used the app (2075/3649, 56.86%), they engaged significantly less with it. Older people and users who were recently diagnosed tended to use the app more actively.

Conclusions

Strategies to increase or sustain the use of apps and availability of health data may target the mode of data collection and content design and should take into account privacy concerns of the users at the same time. Users' engagement was determined by various user characteristics, indicating that particular patient groups should be targeted or assisted when integrating apps into the self-management of their disease.

SUBMITTER: Bohm AK

PROVIDER: S-EPMC7679206 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Publications

Real-World Evidence of User Engagement With Mobile Health for Diabetes Management: Longitudinal Observational Study.

Böhm Anna-Katharina AK Jensen Morten Lind ML Sørensen Mads Reinholdt MR Stargardt Tom T

JMIR mHealth and uHealth 20201106 11

<h4>Background</h4>Patient support apps have risen in popularity and provide novel opportunities for self-management of diabetes. Such apps offer patients to play an active role in monitoring their condition, thereby increasing their own treatment responsibility. Although many health apps require active user engagement to be effective, there is little evidence exploring engagement with mobile health (mHealth).<h4>Objective</h4>This study aims to analyze the extent to which users engage with mHea ...[more]

PMID: 32975198

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Project description:BACKGROUND:The literature suggests that the product design of self-guided electronic health (eHealth) interventions impacts user engagement. Traditional trial settings, however, do not enable the examination of these relationships in real-world use. OBJECTIVE:This study aimed to examine whether the qualities of product design, research evidence, and publicly available data predict real-world user engagement with mobile and Web-based self-guided eHealth interventions. METHODS:This analysis included self-guided mobile and Web-based eHealth interventions available to the public-with their qualities assessed using the Enlight suite of scales. Scales included Usability, Visual Design, User Engagement, Content, Therapeutic Persuasiveness, Therapeutic Alliance, Credibility, and Research Evidence. Behavioral data on real-world usage were obtained from a panel that provides aggregated nonpersonal information on user engagement with websites and mobile apps, based on a time window of 18 months that was set between November 1, 2016 and April 30, 2018. Real-world user engagement variables included average usage time (for both mobile apps and websites) and mobile app user retention 30 days after download. RESULTS:The analysis included 52 mobile apps (downloads median 38,600; interquartile range [IQR] 116,000) and 32 websites (monthly unique visitors median 5689; IQR 30,038). Results point to moderate correlations between Therapeutic Persuasiveness, Therapeutic Alliance, and the 3 user engagement variables (.31?rs?.51; Ps?.03). Visual Design, User Engagement, and Content demonstrated similar degrees of correlation with mobile app engagement variables (.25?rs?.49; Ps?.04) but not with average usage time of Web-based interventions. Positive correlations were also found between the number of reviews on Google Play and average app usage time (r=.58; P<.001) and user retention after 30 days (r=.23; P=.049). Although several product quality ratings were positively correlated with research evidence, the latter was not significantly correlated with real-world user engagement. Hierarchical stepwise regression analysis revealed that either Therapeutic Persuasiveness or Therapeutic Alliance explained 15% to 26% of user engagement variance. Data on Google Play (number of reviews) explained 15% of the variance of mobile app usage time above Enlight ratings; however, publicly available data did not significantly contribute to explaining the variance of the other 2 user-engagement variables. CONCLUSIONS:Results indicate that the qualities of product design predict real-world user engagement with eHealth interventions. The use of real-world behavioral datasets is a novel way to learn about user behaviors, creating new avenues for eHealth intervention research.

Project description:BackgroundPatient-reported outcomes (PROs) capture patients' views on their health conditions and its management, and are increasingly used in clinical trials, including those targeting type 2 diabetes (T2D). Mobile health (mHealth) tools offer novel solutions for collecting PRO data in real time. Although patients are at the center of any PRO-based intervention, few studies have examined user engagement with PRO mHealth tools.ObjectiveThis study aimed to evaluate user engagement with a PRO mHealth tool for T2D management, identify patterns of user engagement and similarities and differences between the patients, and identify the characteristics of patients who are likely to drop out or be less engaged with a PRO mHealth tool.MethodsWe extracted user engagement data from an ongoing clinical trial that tested the efficacy of a PRO mHealth tool designed to improve hemoglobin A1c levels in patients with uncontrolled T2D. To date, 61 patients have been randomized to the intervention, where they are sent 6 PRO text messages a day that are relevant to T2D self-management (healthy eating and medication adherence) over the 12-month study. To analyze user engagement, we first compared the response rate (RR) and response time between patients who completed the 12-month intervention and those who dropped out early (noncompleters). Next, we leveraged latent class trajectory modeling to classify patients from the completer group into 3 subgroups based on similarity in the longitudinal engagement data. Finally, we investigated the differences between the subgroups of completers from various cross-sections (time of the day and day of the week) and PRO types. We also explored the patient demographics and their distribution among the subgroups.ResultsOverall, 19 noncompleters had a lower RR to PRO questions and took longer to respond to PRO questions than 42 completers. Among completers, the longitudinal RRs demonstrated differences in engagement patterns over time. The completers with the lowest engagement showed peak engagement during month 5, almost at the midstage of the program. The remaining subgroups showed peak engagement at the beginning of the intervention, followed by either a steady decline or sustained high engagement. Comparisons of the demographic characteristics showed significant differences between the high engaged and low engaged subgroups. The high engaged completers were predominantly older, of Hispanic descent, bilingual, and had a graduate degree. In comparison, the low engaged subgroup was composed mostly of African American patients who reported the lowest annual income, with one of every 3 patients earning less than US $20,000 annually.ConclusionsThere are discernible engagement phenotypes based on individual PRO responses, and their patterns vary in the timing of peak engagement and demographics. Future studies could use these findings to predict engagement categories and tailor interventions to promote longitudinal engagement.Trial registrationClinicaltrials.gov NCT03652389; https://clinicaltrials.gov/ct2/show/NCT03652389.International registered report identifier (irrid)RR2-10.2196/18554.

Project description:BackgroundHealthcare stakeholders have pronounced both enthusiasm and apprehension over the expanding use of real-world evidence (RWE). The patient community-those who benefit from new treatments but are vulnerable to potential safety risks and whose routine medical encounters are used to generate RWE-has been less vocal. Understanding patient perspectives on the use of RWE to guide clinical decision making and inform regulatory decisions and value assessments is imperative.MethodsWe convened a day-long, multi-stakeholder roundtable in Washington D.C., USA, on 31 July 2017 to gather patient-community views on RWE and related concerns and the communications, information and tools needed by patients to understand, trust, and use RWE. Participants included a convenience sample of National Health Council (NHC) members primarily representing patient groups as well as non-patient members with an interest in RWE. Participants were organized into small, pre-assigned groups, ensuring representativeness across stakeholders and patient leadership. Discussions, including storyboards, notes, and illustrative examples were captured and later analyzed thematically by NHC staff.ResultsTen RWE themes emerged: (1) most patients were unaware of RWE and its actual or potential uses, (2) common definitions for real-world data and RWE are needed, (3) patient organizations need RWE skills and tools, (4) patient-scientist partnerships can help differentiate high-quality RWE, (5) RWE should inform decision making, (6) clinician support is needed for RWE uptake in patient decision making, (7) communications to patients should be balanced and empowering, (8) context of use impacts RWE acceptability/trust, (9) privacy/data ownership require clarity, and (10) patient-generated data are also real-world data (RWD).ConclusionPatients see great possibility in using RWE to understand how a treatment works-to find someone that "looks like me" as assurance of how a treatment might benefit them personally. Patient groups will play a critical role in helping to educate constituents on understanding, contributing to, and using RWE. To maximize patient uptake and the co-development and application of RWE, patient groups require education and tools.

Project description:BackgroundDigital health services can serve as scalable solutions to address the growing demand for mental health care. However, more research is needed to better understand the association between engagement with care and improvements in subclinical outcomes.ObjectiveThis study aims to fill this research gap by examining the relationship between members' engagement with the Ginger platform and changes in their psychological resilience.MethodsWe conducted a retrospective observational study of 3272 members who accessed Ginger, an on-demand mental health service, between January 2021 and November 2021. Each member completed the 10-item Connor-Davidson Resilience Scale questionnaire, a measure of psychological resilience, at baseline and again during a 6- to 16-week follow-up window. Depression and anxiety symptoms (9-item Patient Health Questionnaire and 7-item Generalized Anxiety Disorder) were also measured. Linear regression was used to identify the association between engagement with Ginger's multiple care modalities and changes in resilience. Moderator analysis was conducted to test whether clinical depression or anxiety at baseline moderated the relationship between engagement level and changes in resilience.ResultsOf the 3272 members, 2683 (82%) reported low resilience at baseline. The mean change in resilience was 0.77 (SD 5.50) points. Linear regression models showed that age and census region did not predict changes in resilience; however, male members showed larger improvements (coefficient=0.58; P=.04). Baseline mental health outcomes, including resilience and depression and anxiety symptoms, were strong predictors of changes in resilience. Every point decrease in baseline resilience is associated with a 0.28-point increase in change in resilience (P<.001), and members with no or mild depression and anxiety at baseline saw changes in resilience that were 1.44 points (P<.001) larger than their clinical counterparts. Engagement with the Ginger system predicted changes in resilience. Members who engaged with Ginger coaching, clinical services, or both improved their resilience by 1.82, 1.55, and 1.40 points, respectively (P<.001), more than those who only engaged with Ginger content. Screening negative for moderate to severe depression and anxiety at baseline was associated with larger improvements in resilience (coefficient=1.30; P<.001); however, subclinical status was not shown to be a moderator for the association between level of engagement and changes in resilience.ConclusionsEngagement with Ginger services was associated with improvements in resilience. Members who engaged in coaching or clinical care had significantly larger improvements compared with those who only engaged in self-guided content, regardless of whether a member screened positive for clinical depression or anxiety at baseline.

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Dataset Information

Real-World Evidence of User Engagement With Mobile Health for Diabetes Management: Longitudinal Observational Study.

Background

Objective

Methods

Results

Conclusions

Publications

Real-World Evidence of User Engagement With Mobile Health for Diabetes Management: Longitudinal Observational Study.

Similar Datasets

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