Phenotypes of engagement with mobile health technology for heart rhythm monitoring.
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ABSTRACT: Objectives
Guided by the concept of digital phenotypes, the objective of this study was to identify engagement phenotypes among individuals with atrial fibrillation (AF) using mobile health (mHealth) technology for 6 months.Materials and methods
We conducted a secondary analysis of mHealth data, surveys, and clinical records collected by participants using mHealth in a clinical trial. Patterns of participants' weekly use over 6 months were analyzed to identify engagement phenotypes via latent growth mixture model (LGMM). Multinomial logistic regression models were fitted to compute the effects of predictors on LGMM classes.Results
One hundred twenty-eight participants (mean age 61.9 years, 75.8% male) were included in the analysis. Application of LGMM identified 4 distinct engagement phenotypes: "High-High," "Moderate-Moderate," "High-Low," and "Moderate-Low." In multinomial models, older age, less frequent afternoon mHealth use, shorter intervals between mHealth use, more AF episodes measured directly with mHealth, and lower left ventricular ejection fraction were more strongly associated with the High-High phenotype compared to the Moderate-Low phenotype (reference). Older age, more palpitations, and a history of stroke or transient ischemic attack were more strongly associated with the Moderate-Moderate phenotype compared to the reference.Discussion
Engagement phenotypes provide a nuanced characterization of how individuals engage with mHealth over time, and which individuals are more likely to be highly engaged users.Conclusion
This study demonstrates that engagement phenotypes are valuable in understanding and possibly intervening upon engagement within a population, and also suggests that engagement is an important variable to be considered in digital phenotyping work more broadly.
SUBMITTER: Lee J
PROVIDER: S-EPMC8200132 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundPediatric blood and marrow transplant (PBMT) patients experience significant symptom distress. Mobile health (mHealth) technologies can be leveraged to improve understanding of the patient's symptom experience by providing continuous, real-time, in situ, patient-generated symptom data. This rich data stream can subsequently enhance symptom management strategies. However, limited research has been conducted in this area.ObjectivesThis pilot study seeks to (a) explore the feasibility of integrating mHealth technologies to monitor symptom data for PBMT patients and (b) evaluate the study design, measures, and procedures.MethodsAn exploratory longitudinal design was employed to assess the feasibility of monitoring 10 PBMT patients' symptoms using data from two mHealth technologies: (a) a smartphone mHealth application (app) to collect symptom data and (b) a wearable tracking device (Apple watch) to collect physiological data. Feasibility was measured as usability and acceptability. Monthly patient interviews and an end-of-study feasibility survey were employed and analyzed to further understand reasons for sustained interest in and attrition from the study.ResultsOverall usability of the wearable was 51%, and app was 56%. Children reported devices were easy to use and acceptable. The study demonstrated acceptability with an enrollment rate of 83% and an attrition rate of 30%, with 70% of the children remaining in the study for at least 40 days.DiscussionThis pilot study is among the first to explore the feasibility of using mobile technologies to longitudinally obtain patient-generated symptom data to enhance understanding of the PBMT symptom experience. In addition, it will improve our understanding of how these data present, interact, and cluster together throughout the posttransplant period.
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Project description:BackgroundAtrial fibrillation (AF) is the most common arrhythmia after cardiac surgery, yet the precise incidence and significance of arrhythmias after discharge home need to be better defined. Photoplethysmography (PPG)-based smartphone apps are promising tools to enable early detection and follow-up of arrhythmias.ObjectiveBy using a PPG-based smartphone app, we aimed to gain more insight into the prevalence of AF and other rhythm-related complications upon discharge home after cardiac surgery and evaluate the implementation of this app into routine clinical care.MethodsIn this prospective, single-center trial, patients recovering from cardiac surgery were asked to register their heart rhythm 3 times daily using a Food and Drug Administration-approved PPG-based app, for either 30 or 60 days after discharge home. Patients with permanent AF or a permanent pacemaker were excluded.ResultsWe included 24 patients (mean age 60.2 years, SD 12 years; 15/23, 65% male) who underwent coronary artery bypass grafting and/or valve surgery. During hospitalization, 39% (9/23) experienced postoperative AF. After discharge, the PPG app reported AF or atrial flutter in 5 patients. While the app notified flutter in 1 patient, this was a false positive, as electrocardiogram revealed a 2nd-degree, 2:1 atrioventricular block necessitating a permanent pacemaker. AF was confirmed in 4 patients (4/23, 17%) and interestingly, was associated with an underlying postoperative complication in 2 participants (pneumonia n=1, pericardial tamponade n=1). A significant increase in the proportion of measurements indicating sinus rhythm was observed when comparing the first to the second month of follow-up (P<.001). In the second month of follow-up, compliance was significantly lower with 2.2 (SD 0.7) measurements per day versus 3.0 (SD 0.8) measurements per day in the first month (P=.002). The majority of participants (17/23, 74%), as well as the surveyed primary care physicians, experienced positive value by using the app as they felt more involved in the postoperative rehabilitation.ConclusionsImplementation of smartphone-based PPG technology enables detection of AF and other rhythm-related complications after cardiac surgery. An association between AF detection and an underlying complication was found in 2 patients. Therefore, smartphone-based PPG technology may supplement rehabilitation after cardiac surgery by acting as a sentinel for underlying complications, rhythm-related or otherwise.
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Project description:ObjectivesSelf-monitoring is recommended for individuals with bipolar disorder, with numerous technological solutions available. This study aimed to identify basic components of these solutions that increase engagement with self-monitoring.MethodsParticipants with bipolar disorder (n = 47) monitored their symptoms with a Fitbit and a smartphone app and were randomly assigned to either review or not review recorded symptoms weekly. We tested whether individuals would better adhere to and prefer monitoring with passive monitoring with an activity tracker compared to active monitoring with a smartphone app and whether individuals would better adhere to self-monitoring if their recorded symptoms were reviewed with an interviewer.ResultsMonitoring with a smartphone app achieved similar adherence and preference to Fitbit (P > .85). Linear mixed effects modeling found adherence decreased significantly more over the study for the Fitbit (12% more, P < .001) even though more participants reported they would use the Fitbit over a year compared to the app (72.3% vs 46.8%). Reviewing symptoms weekly did not improve adherence, but most participants reported they would prefer to review symptoms with a clinician (74.5%) and on monthly basis (57.5%) compared to alternatives. Participants endorsed sleep as the most important symptom to monitor, forgetfulness as the largest barrier to self-monitoring, and raising self-awareness as the best reason for self-monitoring.ConclusionsWe recommend a combined strategy of wearable and mobile monitoring that includes reminders, targets raising self-awareness, and tracks sleep. A clinician may want to review symptoms on a monthly basis.Trial registrationClinicalTrials.gov NCT03358238.
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Project description:BACKGROUND:Monitoring signs and symptoms in bipolar disorder (BP) is typically based on regular assessments from patient-clinician interactions. Mobile and wearable technology promises to make monitoring symptoms in BP easier, but little is known about how best to engage individuals with BP in monitoring symptoms. OBJECTIVE:The objective of this study was to provide the rationale and protocol for a randomized controlled trial that investigates engagement strategies for monitoring symptoms of BP, including the strategies of using activity trackers compared with self-reports and reviewing recorded symptoms weekly with an interviewer. METHODS:A total of 50 individuals with BP will be recruited from the Prechter Longitudinal Study of Bipolar Disorder at the University of Michigan to participate in a 6-week study. Participants will monitor their symptoms through an activity tracker (Fitbit Alta HR) and a mobile phone app designed for this study. In addition to monitoring symptoms, participants have a 50-50 chance of being assigned to an arm that reviews self-reports and activity information weekly. Statistical tests will be performed to test hypotheses that participants adhere to activity tracking significantly more than self-reporting, prefer activity tracking significantly more than self-reporting, and better adhere to both activity tracking and self-reporting when reviewing collected information weekly. RESULTS:Recruitment commenced in November 2017. The first group of participants began the study in January 2018. CONCLUSIONS:This study aims to establish strategies to engage individuals with BP in monitoring their symptoms with mobile and wearable technology. Better engagement strategies are expected to aid current efforts in bipolar research and clinical care, from the development of new mobile phone apps to providing the right intervention to the right individual at the right moment. TRIAL REGISTRATION:ClinicalTrials.gov NCT03358238; https://clinicaltrials.gov/ct2/show/NCT03358238 (Archived by WebCite at http://www.webcitation.org/6yebuNfz5). REGISTERED REPORT IDENTIFIER:RR1-10.2196/9899.
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Project description:ObjectivesTo assess smartphone ownership, use of mobile health (mHealth) applications, and willingness to use this technology to facilitate medication management after kidney transplantation.MethodsA survey was developed with the use of previously validated questions and administered to stable adult kidney recipients from May to July 2015. Descriptive and comparative statistics were used to assess willingness to utilize mHealth technology as it related to sociodemographics, medication adherence, and medication side effects. Comparisons were also made to a survey administered in 2012. The primary outcome was the incidence of cell phone and smartphone ownership, willingness to use mHealth, immunosuppressant side effects, and self-reported nonadherence.ResultsA total of 142 patients were approached, and 139 (98%) agreed to participate; 96% of respondents indicated mobile phone ownership, 61% owned a smartphone, 30% had prior knowledge of mHealth, and 7% were already using an mHealth app; 78% reported a positive attitude toward the use of mHealth for medication management. Smartphone ownership has nearly doubled since 2012 (61% vs. 35%; P <0.001). Patients <55 years of age were more likely to own smartphones (75% vs. 46%; P <0.001) and to strongly agree with the use of mHealth (62% vs. 36%; P = 0.015). Self-reported nonadherence or severe medication side effects did not appreciably influence a patient's willingness to use mHealth.ConclusionAmong recipients of kidney transplants, smartphone ownership has dramatically increased, and recipients have a positive attitude toward the use of mHealth for medication management.
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Project description:BackgroundTracking individuals in environmental epidemiological studies using novel mobile phone technologies can provide valuable information on geolocation and physical activity, which will improve our understanding of environmental exposures.ObjectiveThe objective of this study was to assess the performance of one of the least expensive mobile phones on the market to track people's travel-activity pattern.MethodsAdults living and working in Barcelona (72/162 bicycle commuters) carried simultaneously a mobile phone and a Global Positioning System (GPS) tracker and filled in a travel-activity diary (TAD) for 1 week (N=162). The CalFit app for mobile phones was used to log participants' geographical location and physical activity. The geographical location data were assigned to different microenvironments (home, work or school, in transit, others) with a newly developed spatiotemporal map-matching algorithm. The tracking performance of the mobile phones was compared with that of the GPS trackers using chi-square test and Kruskal-Wallis rank sum test. The minute agreement across all microenvironments between the TAD and the algorithm was compared using the Gwet agreement coefficient (AC1).ResultsThe mobile phone acquired locations for 905 (29.2%) more trips reported in travel diaries than the GPS tracker (P<.001) and had a median accuracy of 25 m. Subjects spent on average 57.9%, 19.9%, 9.0%, and 13.2% of time at home, work, in transit, and other places, respectively, according to the TAD and 57.5%, 18.8%, 11.6%, and 12.1%, respectively, according to the map-matching algorithm. The overall minute agreement between both methods was high (AC1 .811, 95% CI .810-.812).ConclusionsThe use of mobile phones running the CalFit app provides better information on which microenvironments people spend their time in than previous approaches based only on GPS trackers. The improvements of mobile phone technology in microenvironment determination are because the mobile phones are faster at identifying first locations and capable of getting location in challenging environments thanks to the combination of assisted-GPS technology and network positioning systems. Moreover, collecting location information from mobile phones, which are already carried by individuals, allows monitoring more people with a cheaper and less burdensome method than deploying GPS trackers.
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Project description:BackgroundSmartphones offer the possibility of assessing recovery of mobility after total hip or knee arthroplasty (THA or TKA) passively and reliably, as well as facilitating the collection of patient-reported outcome measures (PROMs) with greater frequency.Questions/purposesWe investigated the feasibility of using mobile technology to collect daily step data and biweekly PROMs to track recovery after total joint arthroplasty.MethodsPre- and post-operative daily steps were recorded in prospectively enrolled patients (128 THA and 139 TKA) via an app, which uses the phone's accelerometer. During 6-month follow-up, patients also completed PROMs (the pain numeric rating scale, the Hip Disability and Osteoarthritis Outcome Score Joint Replacement [HOOS JR] and the Knee Injury and Osteoarthritis Outcome Score Joint Replacement [KOOS JR]), and HOOS or KOOS JR quality of life domain via a mobile-enabled web link.ResultsAt least 6 months of follow-up was completed by 65% for THA and 68% for TKA patients. Reasons for non-completion included time commitment, phone battery, app issues, and health complications. Responses from 78% of requested PROMs were returned with 96% of patients returning at least one post-operative PROM. Step data were available from 92% of days from male patients and 86% of days from female patients. The most robust recovery occurred early, within the first 2 months. The groups with higher pre-operative steps were more likely to recover their maximum daily steps at an earlier time point. Correlations between step counts and PROMs scores were modest.ConclusionAssessing large amounts of post-TKA and post-THA step data using mobile technology is feasible. Completion rates were good, making the technology very useful for collecting frequent PROMs. Being unable to ensure that patients always carried their phones limited our analysis of the step counts.
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Project description:BACKGROUND:Digital health technologies, including telemedicine, mobile health (mHealth), and remote monitoring, are playing a greater role in medical practice. Safe and accurate management of medical information leads to the advancement of digital health, which in turn results in a number of beneficial effects. Furthermore, mHealth can help lower costs by facilitating the delivery of care and connecting people to their health care providers. Mobile apps help empower patients and health care providers to proactively address medical conditions through near real-time monitoring and treatment, regardless of the location of the patient or the health care provider. Additionally, mHealth data are stored in servers, and consequently, data management that prevents all forms of manipulation is crucial for both medical practice and clinical trials. OBJECTIVE:The aim of this study was to develop and evaluate a tamper-resistant mHealth system using blockchain technology, which enables trusted and auditable computing using a decentralized network. METHODS:We developed an mHealth system for cognitive behavioral therapy for insomnia using a smartphone app. The volunteer data collected with the app were stored in JavaScript Object Notation format and sent to the blockchain network. Thereafter, we evaluated the tamper resistance of the data against the inconsistencies caused by artificial faults. RESULTS:Electronic medical records collected using smartphones were successfully sent to a private Hyperledger Fabric blockchain network. We verified the data update process under conditions where all the validating peers were running normally. The mHealth data were successfully updated under network faults. We further ensured that any electronic health record registered to the blockchain network was resistant to tampering and revision. The mHealth data update was compatible with tamper resistance in the blockchain network. CONCLUSIONS:Blockchain serves as a tamperproof system for mHealth. Combining mHealth with blockchain technology may provide a novel solution that enables both accessibility and data transparency without a third party such as a contract research organization.
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Project description: Not available
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