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Smartphone apps and mobile health devices offer innovative ways to collect longitudinal cardiovascular data. Randomized evidence regarding effective strategies to maintain longitudinal engagement is limited.
This study aimed to evaluate smartphone messaging interventions on remote transmission of blood pressure (BP) and heart rate (HR) data.
We conducted a 2 × 2 × 2 factorial blinded randomized trial with randomization implemented centrally to ensure allocation concealment. We invited participants from the Electronic Framingham Heart Study (eFHS), an e-cohort embedded in the FHS, and asked participants to measure their BP (Withings digital cuff) weekly and wear their smartwatch daily. We assessed 3 weekly notification strategies to promote adherence: personalized versus standard; weekend versus weekday; and morning versus evening. Personalized notifications included the participant’s name and were tailored to whether or not data from the prior week were transmitted to the research team. Intervention notification messages were delivered weekly automatically via the eFHS app. We assessed if participants transmitted at least one BP or HR measurement within 7 days of each notification after randomization. Outcomes were adherence to BP and HR transmission at 3 months (primary) and 6 months (secondary).
Of the 791 FHS participants, 655 (82.8%) were eligible and randomized (mean age 53, SD 9 years; 392/655, 59.8% women; 596/655, 91% White). For the personalized versus standard notifications, 38.9% (126/324) versus 28.8% (94/327) participants sent BP data at 3 months (difference=10.1%, 95% CI 2.9%-17.4%;
Personalized notifications increased longitudinal adherence to BP and HR transmission from mobile and digital devices among eFHS participants. Our results suggest that personalized messaging is a powerful tool to promote adherence to mobile health systems in cardiovascular research.
ClinicalTrials.gov NCT03516019; https://clinicaltrials.gov/ct2/show/NCT03516019
Digital technologies offer new opportunities to collect epidemiologic data and real-world evidence. Smartphones, smartwatches, and wearables have increasing penetration and use [
However, participant retention and engagement is a major challenge in epidemiological and clinical trials deploying surveys or interventions with digital technologies. In the MyHeart Counts Cardiovascular Health Study, there was a rapid drop-off observed in user engagement with app use after approximately 4 days [
We conducted a randomized controlled trial to test the effect of smartphone app notification messaging strategies on improving participants’ long-term (3 months) use and return of HR and blood pressure (BP) data. The trial was embedded in the electronic Framingham Health Study (eFHS), an e-cohort of participants from the FHS, using a smartphone app and digital devices [
We conducted a 2 × 2 × 2 factorial randomized trial embedded in the eFHS. The trial was registered at ClinicalTrials.gov (NCT03516019).
This study was approved by the Boston University Medical Campus Institutional Review Board (H-36586).
FHS Third Generation (Gen 3; n=4095), Omni Group 2 (n=410), and New Offspring Spouse (n=103) cohorts were enrolled from 2002 to 2005 and have been examined every 6 to 8 years at the FHS research center. Participants in the eFHS were enrolled from the Gen 3, Omni Group 2, and New Offspring Spouse cohorts during the in-person examination 3 (2016-2019) at the FHS Research Center in Framingham, Massachusetts, United States [
At the time of the research exam, the study technician invited participants to download the eFHS app. The eFHS app allows communication with participants through notifications, permitting us to send the messaging intervention notifications defined below. Participants were asked to answer health surveys administered through the app at baseline and every 3 months. In addition, participants with iPhones were provided with choices to pair the eFHS app with a Withings-Nokia BP cuff and an Apple Watch (series 0; Apple Inc). Participants were trained in the use of the devices and asked to wear the watch daily and send a BP measurement once per week. Participants were provided with written instructions if they preferred remote enrollment. The app automatically transmits data, such as HR or BP measurements, to the FHS research center if participants have paired their devices with their iPhone.
We enrolled participants in the messaging trial between April 13, 2018, and February 8, 2019, and completed the follow-up of all enrolled participants by March 23, 2019, for the primary outcome. We invited all new eFHS enrollees to participate in the messaging trial during their in-person examination 3 at the FHS research center. In addition, we contacted eligible participants who had been enrolled in the eFHS prior to the onset of the messaging trial (n=586) by email and phone to invite them to participate (
Participant flow diagram. eFHS: electronic Framingham Health Study; FHS: Framingham Health Study; Gen 3: Third Generation.
Prior to the current messaging trial, all eFHS participants received the following types of standard notifications through the eFHS app: (1) “Welcome to eFHS,” (2) “New surveys are available,” (3) “Reminder to complete surveys,” (4) “Surveys due,” and (5) “Thank you for completing surveys.” In addition, standard notifications were sent if no device data were received in the previous 2 weeks (
We sent weekly notifications through the app focusing on the following three comparisons: (1) personalized motivational reminder messaging versus standard messaging, (2) messaging sent on a weekend versus weekday, and (3) messaging sent in the morning versus the evening
Intervention groups in the 2 × 2 × 2 factorial design of the electronic Framingham Health Study messaging trial and the number of participants. Sat: Saturday; Wed: Wednesday.
The standard notification invited participants to wear the watch daily and measure their BP weekly and was sent as a single message as follows: “We appreciate your involvement in the eFHS. Please wear your watch daily and measure your blood pressure weekly.” To personalize notifications, we included the participant’s name and customized the messaging content to whether or not the participant’s data were received in the prior week. For example, if data had not been received from the watch, the following message type was sent: “Mr X [FHS last name], we haven’t received data from your apple watch since [mm/dd/yy]. If you need help to reconnect, will you please call 508-935-xxxx or email xxxxx@bu.edu?” If data had already been received, the message was as follows: “Mr X [FHS last name] we have been receiving data from your apple watch. Keep up the good work!” One set of personalized messages targeted the use of the watch, and the other targeted the use of the BP cuff. The 2 messages (one for the watch and one for BP) were sent each week, with the message order alternating each week. Finally, to reduce notification fatigue, the specific messages were drawn at random from a library of personalized notification templates we developed with alternative motivational content (
We chose specific days and times for the messaging strategies based on descriptive data collected in the eFHS between June 2016 and July 2017, reflecting the use of the devices as the day of week and time of day of digital interventions varied across published studies without a clear consensus [
For the primary outcomes, we assessed if participants transmitted at least one BP or HR measurement within 7 days of each notification 3 months after randomization (after 12 notifications). In secondary analyses, we examined the transmission of BP and HR measurements at 1 month and 6 months after random allocation (after 4 and 24 notifications, respectively). We also performed a longitudinal analysis of the repeated weekly transmissions.
Although the notifications did not directly encourage adherence of survey responses (they only referred to HR and BP data transmission), we hypothesized that participants who are more engaged with the devices are more likely to return the 3-month survey. As a consequence, we also examined the effect of the messaging interventions on survey completion at 3 months. We conducted this exploratory analysis only among the newly enrolled eFHS individuals in this trial, because these participants were eligible to receive the first 3-month smartphone survey. Randomization was stratified according to enrollment status (new to eFHS vs previously enrolled).
Based on preliminary data from June 2016 to July 2017, the proportion of participants transmitting data at 3 months from the watch and the cuff was about 50% [
We randomly allocated each participant to 1 of 8 groups. Randomization was stratified according to sex, age (≤55 years vs >55 years), and enrollment in the eFHS prior to the beginning of the current messaging trial. A statistician (LT) generated blocked randomization lists for each stratum. Randomization was implemented centrally by CareEvolution through the eFHS app, ensuring allocation concealment. Research staff enrolled participants in the FHS research center before random allocation to one of the intervention groups, which occurred afterward. eFHS researchers, statistician, research assistant, and research center staff were masked to group assignment. As part of the eFHS, support staff helped participants complete their remote monitoring and data transmission. The support staff used standardized scripts to interact with participants over the phone. To limit the possibility of encouraging participants to use the device, we trained the support staff not to ask participants about the notification messaging content.
Baseline characteristics of participants are presented as mean (SD) for continuous variables or percentage for categorical variables. Characteristics were obtained using standard protocols and definitions from examination 3 (
Of the 791 eligible FHS participants, we received consent from and randomly allocated 655 (82.8%) participants (
Characteristics of the 655 participantsa enrolled in the electronic Framingham Health Study (eFHS) messaging trial 2018-2019.
Variable | Value (N=655) |
Age (years), mean (SD) | 53 (9) |
Age, >55 years, n (%) | 301 (46) |
Women, n (%) | 392 (59.8) |
Multiethnic/multiracial Omni group 2 participants, n (%) | 59 (9) |
Body mass index (kg/m2), mean (SD) | 28 (5) |
Systolic BP (mmHg), mean (SD) | 119 (14) |
Diastolic BP (mmHg), mean (SD) | 76 (8) |
Physical activity index, mean (SD) | 33 (5) |
Current smoking, n (%) | 32 (4.9) |
Diabetes, n (%) | 40 (6.1) |
Hypertension, n (%) | 185 (28.2) |
Prior cardiovascular disease, n (%) | 27 (4.1) |
aIn all, 450 participants had already been enrolled in the eFHS prior to the beginning of the randomized messaging trial, and 205 participants were new eFHS participants. Physical activity was assessed using the FHS physical activity index, a composite score based on the number of hours spent sleeping or in sedentary, slight, moderate, and heavy activities during a 24-hour period. Weights of 1, 1.1, 1.5, 2.4, and 5 were assigned to sleep, sedentary, slight, moderate, and heavy activity, respectively.
At 3 months after randomization, the proportion of participants who transmitted BP measurements was larger in the personalized messaging group compared to the standard messaging group (126/324, 38.9% vs 94/327, 28.8%), for an absolute difference of 10.1% (95% CI 2.9%-17.4%;
There was no evidence of interaction between the 3 types of messaging interventions (personalized vs standard, weekend vs weekday, and morning vs evening;
In the longitudinal analysis of weekly transmission, there was also evidence that the proportion of participants who transmitted BP measurements was larger in the personalized messaging group compared to the standard messaging group over 24 weeks (
Comparisons of proportions of participants transmitting blood pressure measurements according to messaging trial assignment.
Comparison, time after random allocation | Proportion transmitting, n/N (%) | Odds ratio (95% CI) | Difference in proportions (%; 95% CI) | |||
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Intervention group | Nonintervention group |
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1 month | 148/326 (45.4) | 101/327 (30.9) | 1.86 (1.35 to 2.56) | 14.5 (7.1 to 21.9) | <.001 |
|
3 months | 126/324 (38.9) | 94/327 (28.8) | 1.58 (1.14 to 2.19) | 10.1 (2.9 to17.4) | .006 |
|
6 months | 107/291 (36.8) | 66/295 (22.4) | 2.02 (1.40 to 2.90) | 14.4 (7.1 to 21.7) | <.001 |
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1 month | 130/326 (39.9) | 119/327 (36.4) | 1.16 (0.85 to 1.59) | 3.5 (–4.0 to 10.9) | .36 |
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3 months | 114/326 (35) | 106/325 (32.6) | 1.11 (0.80 to 1.54) | 2.4 (–4.9 to 9.6) | .53 |
|
6 months | 93/293 (31.7) | 80/293 (27.3) | 1.24 (0.87 to 1.77) | 4.4 (–2.9 to 11.8) | .24 |
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1 month | 125/325 (38.5) | 124/328 (37.8) | 1.03 (0.75 to 1.41) | 0.7 (–6.8 to 8.1) | .86 |
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3 months | 111/324 (34.3) | 109/327 (33.3) | 1.04 (0.75 to 1.44) | 0.9 (–6.3 to 8.2) | .80 |
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6 months | 92/289 (31.8) | 81/297 (27.3) | 1.25 (0.87 to 1.78) | 4.6 (–2.8 to 11.9) | .23 |
Proportion of participants transmitting at least one blood pressure measurement within 7 days of each weekly notification in the personalized versus standard messaging groups.
At 3 months after randomization, there was no evidence of a difference in the proportions of participants transmitting HR measurements for any of the intervention: personalized versus standard notification (212/324, 65.4% vs 209/327, 63.9%;
There was no evidence of interaction between interventions (
Comparisons of proportions of participants transmitting heart rate measurements according to messaging trial assignment.
Comparison, time after random allocation | Proportion transmitting, n (%) | Odds ratio (95% CI) | Difference in proportions (%; 95% CI) | |||||||
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Intervention group | Nonintervention group |
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1 month | 230/326 (70.6) | 212/327 (64.8) | 1.30 (0.94 to 1.81) | 5.7 (–1.4 to 12.9) | .12 | ||||
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3 months | 212/324 (65.4) | 209/327 (63.9) | 1.07 (0.78 to 1.47) | 1.5 (–5.8 to 8.9) | .69 | ||||
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6 months | 186/281 (66.2) | 158/281 (56.2) | 1.52 (1.08 to 2.15) | 10 (2.0 to 18.0) | .02 | ||||
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1 month | 231/326 (70.9) | 212/327 (64.8) | 1.34 (0.96 to 1.86) | 6.3 (–0.8 to 13.5) | .08 | ||||
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3 months | 212/326 (65) | 209/325 (64.3) | 1.03 (0.75 to 1.42) | 0.7 (–8.1 to 6.6) | .85 | ||||
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6 months | 181/280 (64.6) | 163/282 (57.8) | 1.34 (0.95 to 1.88) | 6.8 (–1.2 to 14.9) | .10 | ||||
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1 month | 228/325 (70.2) | 214/328 (65.2) | 1.25 (0.90 to 1.74) | 4.9 (–2.3 to 12.1) | .18 | ||||
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3 months | 210/324 (64.8) | 211/327 (64.5) | 1.01 (0.73 to 1.40) | 0.3 (–7.1 to 7.6) | .94 | ||||
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6 months | 179/276 (64.9) | 165/286 (57.7) | 1.35 (0.96 to 1.90) | 7.2 (–0.9 to 15.2) | .08 |
Proportion of participants transmitting at least one heart rate measurement within 7 days of each weekly notification in the personalized versus standard messaging groups.
Among 205 participants who had not been enrolled in the eFHS prior to the beginning of the messaging trial, there was no evidence of a difference between intervention groups in terms of survey completion. In the personalized notification group, 58.8% (60/102) and 41.2% (42/102) of participants had complete and missing survey response at 3 months, respectively, as opposed to 57.3% (59/103) and 42.7% (44/103) in the standard notification group (
We evaluated 3 smartphone app notification intervention strategies sent to eFHS participants in a randomized trial aimed at improving the use of a smartwatch and a digital BP cuff for the remote monitoring of HR and BP. We observed evidence that personalized motivational notifications increased adherence over 3 months for BP data transmission and over 6 months for BP and HR transmission. Personalization included the participant’s name, and the message content was contextualized to the individual’s device use for each week of the trial. The use of the smartwatch and the BP cuff decreased over time, but the proportions of participants transmitting BP and HR data were about 10% higher in the personalized versus standard notification groups. There was little or no evidence that morning versus evening notifications or weekend versus weekday notifications were associated with adherence. In an exploratory aim, we did not observe a difference in smartphone app survey completion between intervention groups, but the analysis may have been underpowered. This trial provides evidence that short personalized motivational messaging offers an easy, scalable strategy to increase adherence with device use that potentially can be used in other large digital intervention studies.
The investigation of a diverse set of digital health studies, including a range of diseases in more than 100,000 participants, revealed early user disengagement with a median study retention across all studies of fewer than 6 days [
We observed that compared to younger participants, older participants were more likely to transmit BP and HR data. This finding appears to be consistent with another study that reported older age was associated with retention time [
Our trial used weekly notifications to enhance the use of digital devices over 6 months to monitor BP and HR. We chose a weekly delivery to limit participant burden and associated notification fatigue observed in other trials. However, future investigations are needed to examine the intensity of notification delivery to determine whether more frequent notifications would result in higher observed device use.
Our trial did not find any clear evidence for an effect of the day of the week or time of day on device use. In contrast, a trial of the effect of notification messaging on engagement with a wellness app showed that the effect was greatest when delivered on the weekend at midday [
Notification content that includes multiple behavior change strategies [
We embedded this trial in the eFHS, which provides several strengths. FHS participants have been enrolled in the parent study for over a decade (first examination from 2002-2005), demonstrate loyalty to the parent study; the participants have developed trust in parent study investigators and staff that may have facilitated higher levels of retention and engagement than seen in other e-cohorts [
Our study also has some limitations that merit comment. We did not adjust for multiplicity related to coprimary BP and HR outcomes. We could have considered a multiplicity testing procedure, such the Holm procedure, to preserve the family-wise error rate and calculated the required sample size for the simple disjunctive power [
Brief nonobtrusive personalized motivational smartphone app notifications delivered once per week significantly increased the use of a smartwatch and wireless BP device in middle-aged to older adults for monitoring cardiovascular measures (HR and BP) over 6 months. These simple prompts can be easily incorporated and scaled by other digital health studies to promote long-term engagement. Larger studies of more diverse participants are needed, as well as further study of the impact of notification strategies for digital and mobile health monitoring on health outcomes.
Script for contacting previously enrolled electronic Framingham Health Study participants to join the messaging trial.
Library of messages used in the trial.
Power calculations.
Participant characteristic definitions.
Characteristics of electronic Framingham Health Study participants using a blood pressure cuff or smartwatch not participating in the trial.
Proportion of participants transmitting at least one blood pressure measurement within 7 days of each weekly notification according to age and electronic Framingham Health Study enrollment status.
Proportion of participants transmitting at least one heart rate measurement within 7 days of each weekly notification according to age and electronic Framingham Health Study enrollment status.
Three-way and two-way interaction analyses for the proportion of participants transmitting at least one blood pressure measurement within 7 days of each weekly notification.
Odds ratios from the two-way interaction analyses for the proportion of participants transmitting at least one blood pressure measurement within 7 days of each weekly notification.
Longitudinal analysis of the weekly proportion of participants transmitting at least one blood pressure measurement within 7 days of each weekly notification.
Proportion of participants transmitting at least one blood pressure measurement within 7 days of each weekly notification in the morning and evening notification groups.
Proportion of participants transmitting at least one blood pressure measurement within 7 days of each weekly notification in the weekend and weekday notification groups.
Three-way and two-way interaction analyses for the proportion of participants transmitting at least one heart rate measurement within 7 days of each weekly notification.
Odds ratios from the two-way interaction analyses for the proportion of participants transmitting at least one heart rate measurement within 7 days of each weekly notification.
Longitudinal analysis of the weekly proportion of participants transmitting at least one heart rate measurement within 7 days of each weekly notification.
Proportion of participants transmitting at least one heart rate measurement within 7 days of each weekly notification in the morning and evening notification groups.
Proportion of participants transmitting at least one heart rate measurement within 7 days of each weekly notification in the weekend and weekday notification groups.
Survey completion among 205 individuals who had not been enrolled in the electronic Framingham Health Study prior to the beginning of the messaging trial.
CONSORT-eHEALTH checklist (V 1.6.1).
blood pressure
electronic Framingham Heart Study
Framingham Heart Study
Third Generation
heart rate
This study was presented as an abstract at the American Heart Association Scientific Sessions 2019 [
This study was supported by an award from the Robert Wood Johnson Foundation (74624) and a grant from the National Heart, Lung, and Blood Institute (NHLBI; R01HL141434). The Framingham Heart Study is supported by a contract from NHLBI (PI VSR 75N92019D00031). Investigator time was supported from the following grants: NHLBI R01HL126911 (EJB), NHLBI 2R01 HL092577 (EJB), National Institute on Aging (NIA) 1R01AG066010 (EJB), American Heart Association 18SFRN34110082 (EJB), NHLBI R01HL126911 (DDM), NHLBI R01HL137734 (DDM), NHLBI R01HL137794 (DDM), NHLBI R01HL13660 (DDM), NHLBI U54-HL 143541 (DDM), and NIA 1U01AG068221 (HL). The Apple Watches were provided to Boston University by the Apple Inc at no cost to the study.
Electronic Framingham Health Study (eFHS) data are available from the FHS and will be deposited in the National Heart, Lung, and Blood Institute (NHLBI) Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) for data sharing.
DDM has received research support from Apple Inc, Bristol-Myers Squibb, Boehringer-Ingelheim, Pfizer, Flexcon, Samsung, Philips Healthcare, and Biotronik and has received consultancy fees from Heart Rhythm Society, Bristol-Myers Squibb, Pfizer, Flexcon, Boston Biomedical Associates, and Rose Consulting. He also declares financial support for serving on the Steering Committee for the GUARD-AF study (NCT04126486) and Advisory Committee for the Fitbit Heart Study (NCT04176926). JMM was a guest lecturer/consultant for Merck Research Laboratories unrelated to this work. CN is an employee of CareEvolution, Inc, a health care technology company. Apple Inc was not involved in the study design, analysis, interpretation, or reporting of study results. Starting 2020, NLS received funding from Novo Nordisk for an investigator-initiated research grant unrelated to the current study. All other authors declare no other conflicts of interest.