Predicting health outcomes with intensive longitudinal data collected by mobile health devices: a functional principal component regression approach.

BACKGROUND: Intensive longitudinal data (ILD) collected in near real time by mobile health devices provide a new opportunity for monitoring chronic diseases, early disease risk prediction, and disease prevention in health research. Functional data analysis, specifically functional principal component analysis, has great potential to abstract trends in ILD but has not been used extensively in mobile health research. OBJECTIVE: To introduce functional principal component analysis (fPCA) and demonstrate its potential applicability in estimating trends in ILD collected by mobile heath devices, assessing longitudinal association between ILD and health outcomes, and predicting health outcomes. METHODS: fPCA and scalar-to-function regression models were reviewed. A case study was used to illustrate the process of abstracting trends in intensively self-measured blood glucose using functional principal component analysis and then predicting future HbA1c values in patients with type 2 diabetes using a scalar-to-function regression model. RESULTS: Based on the scalar-to-function regression model results, there was a slightly increasing trend between daily blood glucose measures and HbA1c. 61% of variation in HbA1c could be predicted by the three preceding months' blood glucose values measured before breakfast (P < 0.0001, [Formula: see text]). CONCLUSIONS: Functional data analysis, specifically fPCA, offers a unique tool to capture patterns in ILD collected by mobile health devices. It is particularly useful in assessing longitudinal dynamic association between repeated measures and outcomes, and can be easily integrated in prediction models to improve prediction precision.

Expanding Technology-Enabled Nurse-Delivered Chronic Disease Care: EXTEND.

Mobile monitoring-enabled technologies could enhance telehealth for chronic illness care. EXTEND is an active comparator randomized trial (N=220) of two 24-month interventions: 1) mobile monitoring as a self-management tool (EXTEND); and 2) a 12-month nurse and pharmacist-delivered telehealth intervention incorporating mobile monitoring, self-management support, and medication management that is followed by a 12-month self-management period (EXTEND Plus). EXTEND Plus is a pragmatic approach to integrating mobile monitoring-enabled telehealth for patients uncontrolled diabetes and hypertension into existing clinical infrastructure.

Mobile Monitoring-Enabled Telehealth for Patients with Complex Chronic Illnesses.

Telehealth has the potential to improve management of poorly controlled chronic diseases relative to clinic-based care alone. Mobile monitoring-enabled technologies could enhance telehealth for chronic illness care. Implementation in practice settings would rely on automated integration of data into the electronic health record (EHR). We describe the integration and visualization of data from four remote monitoring devices into the EHR that is coupled with the evaluation of an evidence-based nurse and pharmacist-led telehealth care model for patients with uncontrolled diabetes and hypertension. Using this new pragmatic infrastructure, clinicians use the EHR to prescribe for patients a suite of devices. Alerts are placed upon the data that notify a clinician when values go above or below set thresholds. These data are visualized in the clinical record and clinicians use the EHR as a tool for efficiently delivering and documenting patient telehealth encounters.

Access to Technology and Digital Literacy as Determinants of Health and Health Care.

Access to and the skills to use technology provide the digital equity necessary for civic and cultural participation, employment, lifelong learning, and access to essential services. However, existing digital disparities and the resultant 'digital divide' risk exacerbating health and health-care inequalities. The COVID-19 pandemic amplified these disparities and accelerated the adoption of technology-driven health care such as telehealth, electronic health records, and digital health technologies. Unfortunately, pre-existing disparities influence the adoption and utilization of these technologies, often leaving disadvantaged groups further behind. Efforts toward digital inclusion, access to technology, and digital literacy are necessary to ensure universal access to and meaningful engagement with digital resources. Nurses play a vital role in promoting digital equity, serving as educators, advocates, and digital navigators, guiding patients through the complexities of the digital health landscape.

Evaluating the Feasibility and Usability of the Disposable Intubation Drape (I-Drape).

In response to the COVID-19 pandemic, several protective barrier enclosures were developed to protect healthcare providers during airway manipulation. A certified registered nurse anesthetist (CRNA) created a barrier, the disposable intubation drape (I-Drape), that addressed limitations in range of motion. A nonrandomized, quasi-experimental design with repeated measures was used to evaluate I-Drape usability. CRNAs implemented I-Drape up to three times. Multilevel modeling was used to analyze the primary outcome: time (in seconds) to successful intubation. An online survey was used to evaluate secondary outcomes of interest: users' perceptions of features such as usability, visibility, and durability. We recruited 23 CRNAs as participants for 59 trials. Overall successful intubation and first-pass success rates were 96.6% and 93.2%, respectively. Time to successful intubation did not significantly decrease (ß = -9.16, P = 0.323) or differ significantly among types of laryngoscopy device and years of experience was not a significant factor. Overall, users favorably rated I-Drape with respect to usability, visibility, durability, and feature utility. This study demonstrated the functionality, success rate, and acceptability of I-Drape. I-Drape can be used safely and efficiently with any type of laryngoscopy device by providers with various experience levels.

A Tailored SMS Text Message-Based Intervention to Facilitate Patient Access to Referred Community-Based Social Needs Resources: Protocol for a Pilot Feasibility and Acceptability Study.

BACKGROUND: Health care providers are increasingly screening patients for unmet social needs (eg, food, housing, transportation, and social isolation) and referring patients to relevant community-based resources and social services. Patients' connection to referred services is often low, however, suggesting the need for additional support to facilitate engagement with resources. SMS text messaging presents an opportunity to address barriers related to contacting resources in an accessible, scalable, and low-cost manner. OBJECTIVE: In this multi-methods pilot study, we aim to develop an automated SMS text message-based intervention to promote patient connection to referred social needs resources within 2 weeks of the initial referral and to evaluate its feasibility and patient acceptability. This protocol describes the intervention, conceptual underpinnings, study design, and evaluation plan to provide a detailed illustration of how SMS technology can complement current social needs screening and referral practice patterns without disrupting care. METHODS: For this pilot prospective cohort study, this SMS text message-based intervention augments an existing social needs screening, referral, and navigation program at a federally qualified health center. Patients who received at least one referral for any identified unmet social need are sent 2 rounds of SMS messages over 2 weeks. The first round consists of 5-10 messages that deliver descriptions of and contact information for the referred resources. The second round consists of 2 messages that offer a brief reminder to contact the resources. Participants will evaluate the intervention via a survey and a semistructured interview, informed by an adapted technology acceptance model. Rapid qualitative and thematic analysis will be used to extract themes from the responses. Primary outcomes are implementation feasibility and patient acceptability. Secondary outcomes relate to intervention effectiveness: self-reported attempt to connect and successful connection to referred resources 2 weeks after the initial referral encounter. RESULTS: The study received regulatory approval in May 2021, and we anticipate enrolling 15-20 participants for this initial pilot. CONCLUSIONS: This protocol presents detailed implementation methods about a novel automated SMS intervention for social care integration within primary care. By sharing the study protocol early, we intend to facilitate the development and adoption of similar tools across different clinical settings, as more health care providers seek to address the unmet social needs of patients. Study findings will provide practical insights into the design and implementation of SMS text message-based interventions to improve social and medical care coordination. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/37316.

A Method to Deliver Automated and Tailored Intervention Content: 24-month Clinical Trial.

BACKGROUND: The use of digital technologies and software allows for new opportunities to communicate and engage with research participants over time. When software is coupled with automation, we can engage with research participants in a reliable and affordable manner. Research Electronic Data Capture (REDCap), a browser-based software, has the capability to send automated text messages. This feature can be used to automate delivery of tailored intervention content to research participants in interventions, offering the potential to reduce costs and improve accessibility and scalability. OBJECTIVE: This study aimed to describe the development and use of 2 REDCap databases to deliver automated intervention content and communication to index participants and their partners (dyads) in a 2-arm, 24-month weight management trial, Partner2Lose. METHODS: Partner2Lose randomized individuals with overweight or obesity and cohabitating with a partner to a weight management intervention alone or with their partner. Two databases were developed to correspond to 2 study phases: one for weight loss initiation and one for weight loss maintenance and reminders. The weight loss initiation database was programmed to send participants (in both arms) and their partners (partner-assisted arm) tailored text messages during months 1-6 of the intervention to reinforce class content and support goal achievement. The weight maintenance and reminder database was programmed to send maintenance-related text messages to each participant (both arms) and their partners (partner-assisted arm) during months 7-18. It was also programmed to send text messages to all participants and partners over the course of the 24-month trial to remind them of group classes, dietary recall and physical activity tracking for assessments, and measurement visits. All text messages were delivered via Twilio and were unidirectional. RESULTS: Five cohorts, comprising 231 couples, were consented and randomized in the Partner2Lose trial. The databases will send 53,518 automated, tailored text messages during the trial, significantly reducing the need for staff to send and manage intervention content over 24 months. The cost of text messaging will be approximately US $450. Thus far, there is a 0.004% known error rate in text message delivery. CONCLUSIONS: Our trial automated the delivery of tailored intervention content and communication using REDCap. The approach described provides a framework that can be used in future behavioral health interventions to create an accessible, reliable, and affordable method for intervention delivery and engagement that requires minimal trial-specific resources and personnel time. TRIAL REGISTRATION: ClinicalTrials.gov NCT03801174; https://clinicaltrials.gov/ct2/show/NCT03801174?term=NCT03801174.

A method for intelligent allocation of diagnostic testing by leveraging data from commercial wearable devices: a case study on COVID-19.

Mass surveillance testing can help control outbreaks of infectious diseases such as COVID-19. However, diagnostic test shortages are prevalent globally and continue to occur in the US with the onset of new COVID-19 variants and emerging diseases like monkeypox, demonstrating an unprecedented need for improving our current methods for mass surveillance testing. By targeting surveillance testing toward individuals who are most likely to be infected and, thus, increasing the testing positivity rate (i.e., percent positive in the surveillance group), fewer tests are needed to capture the same number of positive cases. Here, we developed an Intelligent Testing Allocation (ITA) method by leveraging data from the CovIdentify study (6765 participants) and the MyPHD study (8580 participants), including smartwatch data from 1265 individuals of whom 126 tested positive for COVID-19. Our rigorous model and parameter search uncovered the optimal time periods and aggregate metrics for monitoring continuous digital biomarkers to increase the positivity rate of COVID-19 diagnostic testing. We found that resting heart rate (RHR) features distinguished between COVID-19-positive and -negative cases earlier in the course of the infection than steps features, as early as 10 and 5 days prior to the diagnostic test, respectively. We also found that including steps features increased the area under the receiver operating characteristic curve (AUC-ROC) by 7-11% when compared with RHR features alone, while including RHR features improved the AUC of the ITA model's precision-recall curve (AUC-PR) by 38-50% when compared with steps features alone. The best AUC-ROC (0.73 ± 0.14 and 0.77 on the cross-validated training set and independent test set, respectively) and AUC-PR (0.55 ± 0.21 and 0.24) were achieved by using data from a single device type (Fitbit) with high-resolution (minute-level) data. Finally, we show that ITA generates up to a 6.5-fold increase in the positivity rate in the cross-validated training set and up to a 4.5-fold increase in the positivity rate in the independent test set, including both symptomatic and asymptomatic (up to 27%) individuals. Our findings suggest that, if deployed on a large scale and without needing self-reported symptoms, the ITA method could improve the allocation of diagnostic testing resources and reduce the burden of test shortages.

Telehealth for the Longitudinal Management of Chronic Conditions: Systematic Review.

BACKGROUND: Extensive literature support telehealth as a supplement or adjunct to in-person care for the management of chronic conditions such as congestive heart failure (CHF) and type 2 diabetes mellitus (T2DM). Evidence is needed to support the use of telehealth as an equivalent and equitable replacement for in-person care and to assess potential adverse effects. OBJECTIVE: We conducted a systematic review to address the following question: among adults, what is the effect of synchronous telehealth (real-time response among individuals via phone or phone and video) compared with in-person care (or compared with phone, if synchronous video care) for chronic management of CHF, chronic obstructive pulmonary disease, and T2DM on key disease-specific clinical outcomes and health care use? METHODS: We followed systematic review methodologies and searched two databases (MEDLINE and Embase). We included randomized or quasi-experimental studies that evaluated the effect of synchronously delivered telehealth for relevant chronic conditions that occurred over ≥2 encounters and in which some or all in-person care was supplanted by care delivered via phone or video. We assessed the bias using the Cochrane Effective Practice and Organization of Care risk of bias (ROB) tool and the certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation. We described the findings narratively and did not conduct meta-analysis owing to the small number of studies and the conceptual heterogeneity of the identified interventions. RESULTS: We identified 8662 studies, and 129 (1.49%) were reviewed at the full-text stage. In total, 3.9% (5/129) of the articles were retained for data extraction, all of which (5/5, 100%) were randomized controlled trials. The CHF study (1/5, 20%) was found to have high ROB and randomized patients (n=210) to receive quarterly automated asynchronous web-based review and follow-up of telemetry data versus synchronous personal follow-up (in-person vs phone-based) for 1 year. A 3-way comparison across study arms found no significant differences in clinical outcomes. Overall, 80% (4/5) of the studies (n=466) evaluated synchronous care for patients with T2DM (ROB was judged to be low for 2, 50% of studies and high for 2, 50% of studies). In total, 20% (1/5) of the studies were adequately powered to assess the difference in glycosylated hemoglobin level between groups; however, no significant difference was found. Intervention design varied greatly from remote monitoring of blood glucose combined with video versus in-person visits to an endocrinology clinic to a brief, 3-week remote intervention to stabilize uncontrolled diabetes. No articles were identified for chronic obstructive pulmonary disease. CONCLUSIONS: This review found few studies with a variety of designs and interventions that used telehealth as a replacement for in-person care. Future research should consider including observational studies and studies on additional highly prevalent chronic diseases.

Integrating Patient-generated Digital Health Data into Electronic Health Records (EHRs) in Ambulatory Care Settings: EHR Vendor Survey and Interviews.

Data traditionally collected in a clinic or hospital setting is now collected electronically in everyday environments from patients, known as patient-generated health data (PGHD). We conducted informal interviews and collected survey data from major ambulatory care EHR vendors that serve the majority of the U.S. market to collect information on how their clients are integrating PGHD into EHRs. Of the 9 EHR vendors contacted, 6 completed the survey and 5 participated in a 45-minute interview. Feedback from the vendors included how PGHD use has steadily risen over the past decade and how the COVID-19 pandemic accelerated PGHD use. Pathways for data from devices or surveys to be brought securely into the EHR are increasing. While promising, adoption of health IT systems has its challenges. There are disparities in EHRs, devices, and applications. We concluded that more supportive policies are needed to advance PGHD integration.

An mHealth Intervention to Improve Medication Adherence and Health Outcomes Among Patients With Coronary Heart Disease: Randomized Controlled Trial.

BACKGROUND: The treatment of many chronic illnesses involves long-term pharmaceutical therapy, but it is an ongoing challenge to find effective ways to improve medication adherence to promote good health outcomes. Cardioprotective medications can prevent the enlargement of harmful clots, cardiovascular symptoms, and poor therapeutic outcomes, such as uncontrolled high blood pressure and hyperlipidemia, for patients with coronary heart disease. Poor adherence to cardioprotective medications, however, has been reported as a global health concern among patients with coronary heart disease, and it is particularly a concern in China. OBJECTIVE: This study aimed to evaluate the efficacy of a mobile health (mHealth) intervention using 2 mobile apps to improve medication adherence and health outcomes. METHODS: A randomized, placebo-controlled, 2-arm parallel study was conducted in a major university-affiliated medical center located in Chengdu, China. Participants were recruited by flyers and health care provider referrals. Each participant was observed for 90 days, including a 60-day period of mHealth intervention and a 30-day period of nonintervention follow-up. The study coordinator used WeChat and Message Express to send educational materials and reminders to take medication, respectively. Participants used WeChat to receive both the educational materials and reminders. Participants in the control group only received educational materials. This study received ethics approval from the Duke Health Institutional Review Board (Pro00073395) on May 5, 2018, and was approved by West China Hospital (20170331180037). Recruitment began on May 20, 2018. The pilot phase of this study was registered on June 8, 2016, and the current, larger-scale study was retrospectively registered on January 11, 2021 (ClinicalTrials.gov). RESULTS: We recruited 230 patients with coronary heart disease. Of these patients, 196 completed the baseline survey and received the intervention. The majority of participants were married (181/196, 92.4%), male (157/196, 80.1%), and lived in urban China (161/196, 82.1%). Participants' average age was 61 years, and half were retired (103/191, 53.9%). More than half the participants (121/196, 61.7%) were prescribed at least 5 medications. The mean decrease in medication nonadherence score was statistically significant at both 60 days (t179=2.04, P=.04) and 90 days (t155=3.48, P<.001). Systolic blood pressure and diastolic blood pressure decreased in the experimental group but increased in the control group. The mean decrease in diastolic blood pressure was statistically significant at both 60 days (t160=2.07, P=.04) and 90 days (t164=2.21, P=.03). The mean decrease in systolic blood pressure was significantly different in the groups at 90 days (t165=3.12, P=.002). CONCLUSIONS: The proposed mHealth intervention can improve medication adherence and health outcomes, including systolic blood pressure and diastolic blood pressure. TRIAL REGISTRATION: ClinicalTrials.gov NCT02793830; https://clinicaltrials.gov/ct2/show/NCT02793830 and ClinicalTrials.gov NCT04703439; https://clinicaltrials.gov/ct2/show/NCT04703439.

Perceptions of Using Multiple Mobile Health Devices to Support Self-Management Among Adults With Type 2 Diabetes: A Qualitative Descriptive Study.

PURPOSE: This study identified facilitators and barriers pertaining to the use of multiple mobile health (mHealth) devices (Fitbit Alta® fitness tracker, iHealth® glucometer, BodyTrace® scale) that support self-management behaviors in individuals with type 2 diabetes mellitus (T2DM). DESIGN: This qualitative descriptive study presents study participants' perceptions of using multiple mobile devices to support T2DM self-management. Additionally, this study assessed whether participants found visualizations, generated from each participant's health data as obtained from the three separate devices, useful and easy to interpret. METHODS: Semistructured interviews were completed with a convenience sample of participants (n = 20) from a larger randomized control trial on T2DM self-management. Interview questions focused on participants' use of three devices to support T2DM self-management. A study team member created data visualizations of each interview participant's health data using RStudio. RESULTS: We identified two themes from descriptions of study participants: feasibility and usability. We identified one theme about visualizations created from data obtained from the mobile devices. Despite some challenges, individuals with T2DM found it feasible to use multiple mobile devices to facilitate engagement in T2DM self-management behaviors. DISCUSSION: As mHealth devices become increasingly popular for diabetes self-management and are integrated into care delivery, we must address issues associated with the use of multiple mHealth devices and the use of aggregate data to support T2DM self-management. CLINICAL RELEVANCE: Real-time patient-generated health data that are easily accessible and readily available can assist T2DM self-management and catalyze conversations, leading to better self-management. Our findings lay an important groundwork for understanding how individuals with T2DM can use multiple mHealth devices simultaneously to support self-management.

Seriously ill pediatric patient, parent, and clinician perspectives on visualizing symptom data.

OBJECTIVE: This study examined the perspectives on the use of data visualizations and identified key features seriously ill children, their parents, and clinicians prefer to see when visualizing symptom data obtained from mobile health technologies (an Apple Watch and smartphone symptom app). MATERIALS AND METHODS: Children with serious illness and their parents were enrolled into a symptom monitoring study then a subset was interviewed for this study. A study team member created symptom data visualizations using the pediatric participant's mobile technology data. Semi-structured interviews were conducted with a convenience sample of participants (n = 14 children; n = 14 parents). In addition, a convenience sample of clinicians (n = 30) completed surveys. Pediatric and parent participants shared their preferences and perspectives on the symptom visualizations. RESULTS: We identified 3 themes from the pediatric and parent participant interviews: increased symptom awareness, communication, and interpretability of the symptom visualizations. Clinicians preferred pie charts and simple bar charts for their ease of interpretation and ability to be used as communication tools. Most clinicians would prefer to see symptom visualizations in the electronic health record. DISCUSSION: Mobile health tools offer a unique opportunity to obtain patient-generated health data. Effective, concise symptom visualizations can be used to synthesize key clinical information to inform clinical decisions and promote patient-clinician communication to enhance symptom management. CONCLUSIONS: Effectively visualizing complex mobile health data can enhance understanding of symptom dynamics and promote patient-clinician communication, leading to tailored personalized symptom management strategies.

Symptom Monitoring in Children With Life-Threatening Illness: A Feasibility Study Using mHealth.

Children with life-threatening illness (C-LTI) experience considerable symptom distress. Mobile technology may offer opportunities to better obtain symptom data that will lead to better symptom management. A mixed-methods study was conducted to explore the feasibility of monitoring and visualizing symptoms using 2 mobile health devices in C-LTI. Participants engaged with the Apple Watch 56% and recorded in the study app 63% of their study days. Our findings showed feasibility of using mobile technology for monitoring symptoms and further explored opportunities to visualize these data showing symptom occurrences, patterns, and trajectories in C-LTI.

The Line Snuggler: A Central Line Bundling Innovation Evaluated in a High-Risk Pediatric Population.

Central line associated blood stream infections and complications in children require prevention strategies related to both traditional childhood activities as well as adverse events in the intensive care unit or bone marrow transplant unit. This study evaluated a nurse-invented product, the Line Snuggler, designed to protect intravenous tubing and central lines from contamination or entanglement. Patients (n = 30) were enrolled following the chemotherapy phase of transplant. Using a pre-post intervention design, each subject served as their own control for the control phase of the study (Days 1-3 without a Line Snuggler) and the intervention phase (Days 4-6 with a Line Snuggler), with bacterial levels of product and sheets tested on Days 1, 3, 4, and 6. At study conclusion, staff (n = 44) and parents/guardians (n = 25) completed an online survey assessing satisfaction with the product, and perceived utilization and safety. Using t tests, the Line Snuggler bacterial levels showed no difference in growth in adenosine triphosphate levels compared with the same patient's sheets, thereby supporting no increased risk of bacterial growth. Both staff and parents/guardians reported high satisfaction with their use of the Line Snuggler and noted the benefit of its protecting and bundling intravenous lines into a single organizer. This innovative product designed by nurses was evaluated as a means to provide exceptional, high-quality care to achieve the best outcomes while eliminating hospital-acquired complications (https://www.linesnugglers.com/).

A randomized feasibility pilot trial of a financial incentives intervention for dietary self-monitoring and weight loss in adults with obesity.

Financial incentives could be used to improve adherence to behavioral weight loss interventions, increasing their effectiveness. This Phase IIb randomized pilot study evaluated the feasibility and acceptability of a study protocol for providing financial incentives for dietary self-monitoring and/or weight loss. Community-dwelling adults with obesity were enrolled in a 24 week, group-based weight loss program. Participants were randomized in a 2 × 2 factorial design to receive financial incentives for both dietary self-monitoring and weekly weight loss, just one, or neither. Participants could earn up to $300, evolving from fixed weekly payments to intermittent, variable payments. The notice of reward was provided by text message. The study was conducted in three successive cohorts to evaluate study procedure changes, including dietary approach, recruitment and retention strategies, text messaging, and incentives. Descriptive statistics calculated separately for each cohort described study performance relative to predefined targets for recruitment, including minority representation; retention; adherence; and weight loss. Acceptability was assessed via postintervention qualitative interviews. In Cohort 1 (n = 34), a low-carbohydrate diet was used. Recruitment, retention, adherence, and weight loss were adequate, but minority representation was not. For Cohort 2 (n = 31), employing an additional recruitment method and switching to a reduced-calorie diet yielded adequate recruitment, minority representation, retention, and adherence but less weight loss. Returning to a low-carbohydrate diet in Cohort 3 (n = 28) yielded recruitment, minority representation, retention, adherence, and weight loss similar to Cohort 2. Participant feedback informed changes to text message timing and content and incentive amount. Through successive cohorts, we optimized recruitment and retention strategies and text messaging. An adequately powered trial is warranted to evaluate the efficacy of these incentive structures for reducing weight. The trial registration number is NCT02691260.

Correction: Evaluating the Feasibility and Acceptability of a Mobile Health-Based Female Community Health Volunteer Program for Hypertension Control in Rural Nepal: Cross-Sectional Study.

[This corrects the article DOI: 10.2196/15419.].

Digital Phenotyping Self-Monitoring Behaviors for Individuals With Type 2 Diabetes Mellitus: Observational Study Using Latent Class Growth Analysis.

BACKGROUND: Sustained self-monitoring and self-management behaviors are crucial to maintain optimal health for individuals with type 2 diabetes mellitus (T2DM). As smartphones and mobile health (mHealth) devices become widely available, self-monitoring using mHealth devices is an appealing strategy in support of successful self-management of T2DM. However, research indicates that engagement with mHealth devices decreases over time. Thus, it is important to understand engagement trajectories to provide varying levels of support that can improve self-monitoring and self-management behaviors. OBJECTIVE: The aims of this study were to develop (1) digital phenotypes of the self-monitoring behaviors of patients with T2DM based on their engagement trajectory of using multiple mHealth devices, and (2) assess the association of individual digital phenotypes of self-monitoring behaviors with baseline demographic and clinical characteristics. METHODS: This longitudinal observational feasibility study included 60 participants with T2DM who were instructed to monitor their weight, blood glucose, and physical activity using a wireless weight scale, phone-tethered glucometer, and accelerometer, respectively, over 6 months. We used latent class growth analysis (LCGA) with multitrajectory modeling to associate the digital phenotypes of participants' self-monitoring behaviors based on their engagement trajectories with multiple mHealth devices. Associations between individual characteristics and digital phenotypes on participants' self-monitoring behavior were assessed by analysis of variance or the Chi square test. RESULTS: The engagement with accelerometers to monitor daily physical activities was consistently high for all participants over time. Three distinct digital phenotypes were identified based on participants' engagement with the wireless weight scale and glucometer: (1) low and waning engagement group (24/60, 40%), (2) medium engagement group (20/60, 33%), and (3) consistently high engagement group (16/60, 27%). Participants that were younger, female, nonwhite, had a low income, and with a higher baseline hemoglobin A1c level were more likely to be in the low and waning engagement group. CONCLUSIONS: We demonstrated how to digitally phenotype individuals' self-monitoring behavior based on their engagement trajectory with multiple mHealth devices. Distinct self-monitoring behavior groups were identified. Individual demographic and clinical characteristics were associated with different self-monitoring behavior groups. Future research should identify methods to provide tailored support for people with T2DM to help them better monitor and manage their condition. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/13517.

Evaluating the Feasibility and Acceptability of a Mobile Health-Based Female Community Health Volunteer Program for Hypertension Control in Rural Nepal: Cross-Sectional Study.

BACKGROUND: Hypertension is a major modifiable risk factor for cardiovascular disease, the world's leading cause of death. The prevalence of hypertension is disproportionately higher in South Asian countries than in other regions of the world. Screening for hypertension in primary care settings remains a challenge in many South Asian countries, including Nepal. Nepal is located in the Himalayan Mountains region, posing significant geographical challenges for its rural citizens to access primary health care and service delivery. This barrier increases the costs and inconvenience for rural Nepalis to access hypertension screening and treatment. As a result, the prevalence of hypertension in Nepal tripled in the last 25 years to 22.4%-38.6%. Nepal's Ministry of Health and Population relies on female community health volunteers to link health centers and communities to provide basic health services. Over 50,000 of these volunteers in Nepal have received basic health care training and are assigned to take care of maternal and child health. Due to limited health care resources, adopting new methods to control hypertension is an urgent need in Nepal. Several recent studies in Nepal have recommended extending the role of female community health volunteers to include hypertension management through blood pressure monitoring and home-based education. OBJECTIVE: The goal of this study was to assess if a mobile health-based female community health volunteer approach of combining the traditional community health volunteer program with digital technologies would be feasible and acceptable in rural Nepal. METHODS: In this study, we recruited 17 female community health volunteers and extended their role from maternal and child health to hypertension management through screening blood pressures. RESULTS: All 17 female community health volunteers successfully measured 1113 rural Nepalis' blood pressures, identified 169 hypertensive patients, and collected health behaviors data of the 169 hypertensive patients. Among the 169 patients, 70% of them had a mobile phone, and 92% were interested in receiving health-related information via a mobile phone. Among those who were interested in receiving information via a mobile phone, 84% preferred voice calls, and 7% and 1% preferred texting and apps, respectively. CONCLUSIONS: Results from this study indicate that a digital health intervention that leverages feature-phones combined with female community health volunteers may be an acceptable and pragmatic way to implement an evidence-based program to reduce hypertension in rural Nepal.

Self-monitoring diabetes with multiple mobile health devices.

OBJECTIVE: The purpose of this study was to examine the use of multiple mobile health technologies to generate and transmit data from diverse patients with type 2 diabetes mellitus (T2DM) in between clinic visits. We examined the data to identify patterns that describe characteristics of patients for clinical insights. METHODS: We enrolled 60 adults with T2DM from a US healthcare system to participate in a 6-month longitudinal feasibility trial. Patient weight, physical activity, and blood glucose were self-monitored via devices provided at baseline. Patients also responded to biweekly medication adherence text message surveys. Data were aggregated in near real-time. Measures of feasibility assessing total engagement in device submissions and survey completion over the 6 months of observation were calculated. RESULTS: It was feasible for participants from different socioeconomic, educational, and racial backgrounds to use and track relevant diabetes-related data from multiple mobile health devices for at least 6 months. Both the transmission and engagement of the data revealed notable patterns and varied by patient characteristics. DISCUSSION: Using multiple mobile health tools allowed us to derive clinical insights from diverse patients with diabetes. The ubiquitous adoption of smartphones across racial, educational, and socioeconomic populations and the integration of data from mobile health devices into electronic health records present an opportunity to develop new models of care delivery for patients with T2DM that may promote equity as well.