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Understanding how engagement in mobile health (mHealth) weight loss interventions relates to weight change may help develop effective intervention strategies.
This study aims to examine the (1) patterns of participant engagement overall and with key intervention components within each intervention arm in the Cell Phone Intervention For You (CITY) trial; (2) associations of engagement with weight change; and (3) participant characteristics related to engagement.
The CITY trial tested two 24-month weight loss interventions. One was delivered with a smartphone app (cell phone) containing 24 components (weight tracking, etc) and included prompting by the app in predetermined frequency and forms. The other was delivered by a coach via monthly calls (personal coaching) supplemented with limited app components (18 overall) and without any prompting by the app. Engagement was assessed by calculating the percentage of days each app component was used and the frequency of use. Engagement was also examined across 4 weight change categories: gained (≥2%), stable (±2%), mild loss (≥2% to <5%), and greater loss (≥5%).
Data from 122 cell phone and 120 personal coaching participants were analyzed. Use of the app was the highest during month 1 for both arms; thereafter, use dropped substantially and continuously until the study end. During the first 6 months, the mean percentage of days that any app component was used was higher for the cell phone arm (74.2%, SD 20.1) than for the personal coaching arm (48.9%, SD 22.4). The cell phone arm used the apps an average of 5.3 times/day (SD 3.1), whereas the personal coaching participants used them 1.7 times/day (SD 1.2). Similarly, the former self-weighed more than the latter (57.1% days, SD 23.7 vs 32.9% days, SD 23.3). Furthermore, the percentage of days any app component was used, number of app uses per day, and percentage of days self-weighed all showed significant differences across the 4 weight categories for both arms. Pearson correlation showed a negative association between weight change and the percentage of days any app component was used (cell phone:
Engagement in CITY intervention was associated with weight loss during the first 6 months. Nevertheless, engagement dropped substantially early on for most intervention components. Prompting may be helpful initially. More flexible and less intrusive prompting strategies may be needed during different stages of an intervention to increase or sustain engagement. Future studies should explore the motivations for engagement and nonengagement to determine meaningful levels of engagement required for effective intervention.
ClinicalTrials.gov NCT01092364; https://clinicaltrials.gov/ct2/show/NCT01092364 (Archived by WebCite at http://www.webcitation.org/72V8A4e5X)
Mobile health (mHealth) technology provides innovative ways to create interventions that may help people lose weight and sustain weight loss [
The effectiveness of behavioral weight loss studies that are delivered in person is known to be moderated by dose [
In this report, we defined engagement specifically as interaction with components of the intervention and then assessed various types of engagement to understand how and whether engagement relates to weight management. Specifically, we defined engagement as the frequency of use of various intervention components of the cell phone app and the attendance of the in-person group sessions and phone counseling calls. We theorized that a higher engagement may reflect individual motivation and lead to a greater commitment for behavioral change and, thus, a higher intervention efficacy in the Cell Phone Intervention For You (CITY) clinical trial.
In the CITY trial, we compared 2 behavioral interventions for weight loss: the cell phone (CP) intervention arm and the personal coaching (PC) arm [
The CITY study was 1 of the 7 trials in the Early Adult Reduction of weight through LifestYle Intervention consortium, sponsored by National Heart Lung and Blood Institute (NHLBI, 5U01HL096720) [
A total of 365 individuals, aged 18 to 35 years, overweight or obese (body mass index [BMI]>25 kg/m2), and currently using a smartphone were enrolled in the study. Individuals were excluded if they were taking weight loss medications, corticosteroids, or had undergone weight loss surgery.
Cell Phone Intervention For You study CONSORT (Consolidated Standards of Reporting Trials) diagram.
Randomization was stratified by gender and BMI (overweight, BMI≥25-30 kg/m2 vs obese, BMI≥30 kg/m2) with equal allocation to each of the 3 study arms.
Full descriptions of the CITY study [
Behavioral change techniques such as self-monitoring, feedback on behavior, goal setting, problem solving, action planning, behavioral contract, comparison of outcomes, incentive, behavior substitution, habit formation, prompts or cues, modeling of behavior, and shaping knowledge were incorporated into components of the intervention (
Participants randomized to the PC intervention arm attended 6 weekly 2-hour group sessions within 2 months of randomization. The sessions included 5 to 10 participants each and were conducted by a coach with registered dietitian training, with multiple years of coaching experience, and trained in motivational interviewing techniques. At the conclusion of all 6 group sessions, participants received a monthly coaching call from the coach for an additional 22 months (21 calls total). No other intervention contact was made between the coach and participants outside of group sessions and monthly phone coaching. To supplement the coaching, PC participants were encouraged to use the CITY smartphone app to track weight, diet, and physical activity. The uploaded weight data allowed the coach to know if a participant was recording weight measurements daily, as recommended, and to discuss such behavior (or lack of it) during the monthly calls.
In contrast to the app used by the CP arm, the app available to PC participants was entirely passive, requiring participants to self-initiate use by opening the app icon. It did not proactively present the user with information, prompt for information, or send reminders to use the app, and thus, it was unlikely to be seen every time participants used their smartphones.
The CP intervention was designed following the same behavioral framework. However, the behavioral framework was implemented for a smartphone, without interaction with a live coach. The delivery mode for the CP intervention was through a fully automated smartphone app that included auditory, vibration, visual, and peripheral prompting intended to encourage use and gather data. This app was designed and developed by the study team. Coaches communicated with the CP participants every 6 months for a quick
The smartphone app had 24 components within 10 behavioral strategies such as tutorials; tips and news; goal-setting; a buddy system; food tracking; physical activity tracking; feedback and challenge games to increase self-monitoring and physical activity; and an
The visual prompts moved the home screen of the app to the smartphone’s foreground (regardless of what other apps the person might be using at that time), displaying the app content along with a 4 2 seconds audio chime and/or a 4 seconds vibration pattern, depending upon the smartphone’s audio settings at the time. The app also included peripheral always-on reminders, achieved in 2 ways: (1) messages appeared on the smartphone’s lock screen, so that every time the smartphone was used and turned on, a CITY message related to tips or motivation for weight loss was visible and (2) participants were requested to set the CITY app to control their smartphone’s home screen
Programmatically, it is beyond the scope of this report to measure the dosage of most components of the app accurately such as the duration of time the app component was used for but rather only initiation or use of the component. This work, therefore, focuses on the app use as a proxy for the level of engagement. The CITY app logged participant use of every major app component-action (eg, obtaining weight from the scale, dietary tracking, and physical activity tracking) for both intervention arms. There were a total of 18 app component-actions logged for the PC arm and 24 actions logged for the CP arm (see
Recognizing that engagement with different components of the intervention demands different amounts of time and effort (ie, attending group session vs weighing self), we evaluated all components of engagement combined and separately for specific app components. For this manuscript, we considered a discrete instance of
We also examined the relationship between categories of weight change and engagement during the 3 study periods. Weight change was grouped into 4 categories: gained (≥2%), stable (±2%), mild loss (lost ≥2% to <5%), and greater loss (lost ≥5%). These categories were chosen to reflect current guidelines that support 2% to 5% weight loss as clinically meaningful and stable weight as within ±2% of weight gain or loss [
To understand whether baseline characteristics were associated with higher levels of engagement during the first 6 months of the intervention, we examined the distribution of selected baseline characteristics across quartiles of the mean number of times any app component was used per day (including self-weighing) for the PC and CP arms separately. Baseline characteristics such as age, gender, race, ethnicity, education, income, weight, BMI, energy expenditure, healthy eating index score, and hypertension status were examined. All statistical tests were two-sided, and a
Similarly, during the first 6 months, the CP arm had a higher mean percentage of days self-weighed compared with the PC arm (mean 57.1%, SD 23.7 vs mean 32.9%, SD 23.3). Within the PC arm, engagement in the face-to-face group coaching sessions was high during the first 6 months (mean 93.3%, SD 15.8), as was engagement with monthly calls and group sessions combined (mean 95.2%, SD 9.6).
The pattern of early reduction in engagement is also observed when we examined the engagement pattern for each of the app components by intervention arm and over time. Overall, not counting the use of the CITY home screen component, the CP arm used the app components about 3.24 times a day during the first 6 months, whereas the PC arm used components about 1.08 times a day during the same timeframe (data not shown).
Demographics by intervention assignment.
Demographic variables | Combined (n=242) | Cell phone (n=122) | Personal coaching (n=120) | |
Mean (SD) | 29.3 (4.2) | 29.2 (4.2) | 29.4 (4.3) | |
Median (Q1a, Q3b) | 29.7 (26.3, 32.8) | 29.6 (26.6, 32.6) | 29.8 (26.2, 33.3) | |
Range | 19.2-36.0 | 19.2-36.0 | 20.0-36.0 | |
Female, n (%) | 169 (69.8) | 84 (68.8) | 85 (70.8) | |
White | 133 (54.9) | 68 (55.7) | 65 (54.1) | |
Black | 90 (37.1) | 42 (34.4) | 48 (40.0) | |
Other | 19 (7.8) | 12 (9.8) | 7 (5.8) | |
Hispanic ethnicity, n (%) | 16 (6.6) | 9 (7.3) | 7 (5.8) | |
Some college or less | 90 (37.1) | 39 (31.9) | 51 (42.5) | |
College degree | 152 (62.8) | 83 (68.0) | 69 (57.5) | |
Working, n (%) | 212 (87.6) | 107 (88.4) | 105 (87.5) | |
Mean (SD) | 100.9 (24.3) | 102.4 (25.2) | 99.3 (23.4) | |
Median (Q1, Q3) | 96.1 (83.1, 116.0) | 97.8 (83.7, 120.4) | 93.5 (83.0, 111.5) | |
Range | 62.7-189.2 | 62.7-177.1 | 64.1-189.2 | |
Mean (SD) | 35.3 (7.9) | 35.7 (8.2) | 34.9 (7.5) | |
Median (Q1, Q3) | 33.1 (29.2, 40.8) | 33.3 (28.9, 41.6) | 32.9 (29.8, 39.3) | |
Range | 24.9-62.4 | 25.1-62.4 | 24.9-58.9 |
aQ1: first quartile.
bQ3: third quartile.
cCalculated as weight in kilograms divided by height in meters squared.
Engagement patterns by arms over time: the pattern of percentage of days any app component, including weighing, was used for each arm over the 24 months, the number of times any app, including weighing, was used, and the percentage of days self-weighing was used. CP: cell phone; PC: personal coaching.
Engagement during months 1 to 6 for cell phone and personal coaching intervention arms.
Engagement measures | Cell phone (n=122) | Personal coaching (n=120) | |
Mean (SD) | 74.2 (20.1) | 48.9 (22.4) | |
Median (Q1a, Q3b) | 78.2 (65.2, 90.1) | 46.7 (29.8, 67.4) | |
n (range) | 114c (16.6-100.0) | 110 (7.2-96.7) | |
Mean (SD) | 5.3 (3.1) | 1.7 (1.2) | |
Median (Q1, Q3) | 4.8 (3.2, 6.7) | 1.4 (0.9, 2.2) | |
n (range) | 114 (0.5, 14.7) | 110 (0.2, 6.6) | |
Mean (SD) | 57.1 (23.7) | 32.9 (23.3) | |
Median (Q1, Q3) | 55.2 (38.7, 76.2) | 25.1 (13.8, 53.0) | |
n (range) | 114 (5.0-100.0) | 110 (1.7-92.6) | |
Mean (SD) | N/Ae | 93.3 (15.8) | |
Median (Q1, Q3) | N/A | 100.0 (100.0, 100.0) | |
n (range) | N/A | 110 (17.0-100.0) | |
Mean (SD) | N/A | 95.2 (9.6) | |
Median (Q1, Q3) | N/A | 100.0 (91.5, 100.0) | |
n (range) | N/A | 110 (46.0-100.0) |
aQ1: first quartile.
bQ3: third quartile.
cParticipants who dropped out before 6 months were not included in engagement calculations.
dGroup sessions were only conducted during the first 2 months.
eN/A: not applicable. Data were not available for the arm because the component was not offered.
Median daily mean use of top 10 app components by intervention arm by time.
App component | Example of engagement | Cell phonea,b | Personal coaching | ||||
Months 1-6 | Months 7-12 | Months 13-24 | Months 1-6 | Months 7-12 | Months 13-24 | ||
CITYc app home screen used | Activated CITY home screen | 1.06 | 0.41 | 0.16 | 0.76 | 0.27 | 0.13 |
Detailed food tracker used | Entered data in detailed food tracker | 0.46 | 0.14 | 0.05 | 0.35 | 0.04 | 0.01 |
Self-weighing component used | Registered weight in app | 0.55 | 0.43 | 0.22 | 0.25 | 0.12 | 0.08 |
Sugar-sweetened beverage tracker used | Entered data in SSBd tracker | 0.4 | 0.09 | <0.01 | 0.01 | <0.01 | <0.01 |
Physical activity tracker used | Entered data in the PAe tracker | 0.31 | 0.03 | <0.01 | 0.01 | <0.01 | <0.01 |
Veggie tracker used | Entered data in veggie tracker | 0.22 | <0.01 | <0.01 | 0.01 | <0.01 | <0.01 |
Meat tracker used | Entered data in meat tracker | 0.2 | 0.01 | <0.01 | <0.01 | <0.01 | <0.01 |
Goals checked off | Checked off a previously set goal | 0.1 | <0.01 | <0.01 | <0.01 | <0.01 | <0.01 |
Fruit tracker used | Entered data in fruit tracker | 0.14 | 0.06 | <0.01 | 0.01 | <0.01 | <0.01 |
“Right now in CITY” viewed | Clicked “Right now in CITY” component | 0.04 | 0.01 | <0.01 | 0.01 | <0.01 | <0.01 |
aMeans were computed as the total number of times each participant used a particular app component during the respective period, divided by the number of days in that period. Then, the median of these means was computed across all participants within cell phone and personal coaching arms separately.
bData were arranged in descending order of use according to the month 1-6 data of the cell phone arm.
cCITY: Cell Phone Intervention For You.
dSSB: sugar-sweetened beverage.
ePA: physical activity.
The second most used app component was the detailed food tracker, with a median daily mean use of 0.46 and 0.35 times per day during the first 6 months in the CP and PC arms, respectively, which is approximately every 2 to 3 days. The detailed food tracker use decreased by more than half during months 7 to 12 and further reduced to about once every 1 to 3 months during the last 12 months in both arms (months 13-24). In the CP arm, where participants were prompted daily to self-weigh, use of the self-weighing component was about every other day during months 1 to 6, which decreased slightly during months 7 to 12 and further reduced to about once every 4 to 5 days during months 13 to 24. For the PC arm participants who did not receive prompting from the smartphone but were encouraged by their coach during monthly calls, the self-weighing component was used about once every 4 days during months 1 to 6 and dropped to about once every 8 days during months 7 to 12 and once every 12 days during months 13 to 24. The CP participants used other components of the app every 2 to 20 days during months 1 to 6, and the use reduced to almost none for the rest of the study. These other components consisted of the sugar-sweetened beverage tracker, physical activity tracker, veggie tracker, meat tracker, goal setter, fruit tracker, and a screen with updates titled
Other than the detailed food tracker and self-weighing, the PC participants rarely used any of the rest of the app components that were available to them during the entire study.
We also examined selected baseline characteristics of mean number of times the app was used per day during the first 6 months in CP and PC arms separately, across the 4 quartiles. None of the characteristics examined appeared to be related to the varying engagement patterns of the participants (see
Overall pattern of prompting and actual use of selected app components within the cell phone arm.
Five measures of engagement over time (months 1-6, 7-12, and 13-24) by weight change category for cell phone and personal coaching intervention arms.
Engagement measures and time | Weight change categories | ||||||||||||
Gained >2% | Gained ≤2% or lost <2% | Lost ≥2% to <5% | Lost ≥5% | ||||||||||
n | Mean (SD) | n | Mean (SD) | n | Mean (SD) | n | Mean (SD) | ||||||
CPd | 31 | 74.4 (17.0) | 41 | 68.5 (21.3) | 20 | 75.4 (23.6) | 22 | 83.4 (15.5) | .04 | −.213 | |||
PCe | 16 | 40.2 (23.0) | 39 | 42.4 (22.5) | 29 | 52.5 (19.6) | 26 | 59.9 (20.4) | .004 | −.319 | |||
CP | 24 | 52.2 (23.6) | 46 | 59.2 (24.3) | 24 | 56.0 (24.9) | 11 | 60.6 (31.5) | .68 | .004 | |||
PC | 27 | 24.3 (19.9) | 44 | 31.8 (23.8) | 21 | 44.2 (26.4) | 13 | 27.7 (13.1) | .02 | −.124 | |||
CP | 30 | 28.7 (24.7) | 43 | 40.9 (25.4) | 13 | 34.2 (21.4) | 10 | 43.3 (20.5) | .15 | −.127 | |||
PC | 43 | 22.0 (21.2) | 32 | 19.0 (18.8) | 15 | 19.7 (20.7) | 8 | 24.8 (19.6) | .86 | .058 | |||
CP | 31 | 5.0 (2.5) | 41 | 4.3 (2.5) | 20 | 6.4 (3.8) | 22 | 6.8 (3.5) | .006 | −.264 | |||
PC | 16 | 1.2 (1.0) | 39 | 1.3 (0.9) | 29 | 1.9 (1.4) | 26 | 2.3 (1.3) | .001 | −.308 | |||
CP | 24 | 1.7 (1.5) | 46 | 1.8 (1.1) | 24 | 1.7 (1.3) | 11 | 2.2 (1.8) | .70 | −.035 | |||
PC | 27 | 0.5 (0.5) | 44 | 0.8 (0.9) | 21 | 1.3 (1.2) | 13 | 0.6 (0.3) | .02 | −.109 | |||
CP | 30 | 0.6 (0.6) | 43 | 0.7 (0.6) | 13 | 0.6 (0.4) | 10 | 0.8 (0.4) | .56 | −.053 | |||
PC | 43 | 0.5 (0.6) | 32 | 0.4 (0.5) | 15 | 0.5 (0.5) | 8 | 0.5 (0.4) | .96 | .042 | |||
CP | 31 | 52.1 (22.4) | 41 | 51.9 (23.9) | 20 | 60.8 (25.6) | 22 | 70.2 (18.8) | .01 | −.297 | |||
PC | 16 | 24.2 (19.2) | 39 | 26.3 (22.6) | 29 | 35.4 (21.3) | 26 | 45.4 (24.0) | .003 | −.354 | |||
CP | 24 | 40.8 (25.6) | 46 | 50.6 (24.1) | 24 | 48.8 (27.0) | 11 | 52.5 (34.0) | .46 | −.031 | |||
PC | 27 | 14.2 (18.6) | 44 | 20.3 (20.2) | 21 | 30.7 (26.1) | 13 | 17.6 (12.5) | .05 | −.139 | |||
CP | 30 | 24.4 (25.2) | 43 | 36.3 (25.8) | 13 | 28.3 (21.8) | 10 | 36.5 (20.6) | .20 | −.109 | |||
PC | 43 | 16.4 (19.8) | 32 | 13.0 (16.2) | 15 | 14.3 (17.8) | 8 | 20.3 (15.9) | .73 | .066 | |||
PC | 16 | 87.5 (22.3) | 39 | 92.3 (17.8) | 29 | 96.5 (8.2) | 26 | 94.8 (14.1) | .29 | −.194 | |||
PC | 16 | 90.6 (14.0) | 39 | 94.2 (10.2) | 29 | 97.4 (5.6) | 26 | 96.9 (7.8) | .09 | −.246 | |||
PC | 27 | 98.7 (4.5) | 44 | 90.9 (21.7) | 21 | 95.2 (16.0) | 13 | 100.0 (0.0) | .13 | −.066 | |||
PC | 43 | 89.6 (18.8) | 32 | 89.8 (18.5) | 15 | 92.9 (15.2) | 8 | 88.6 (18.2) | .92 | .019 |
a
bPearson correlation coefficient for measuring linear association between engagement and percentage change in weight over time (where weight loss is indicated by a percentage change less than zero; a negative correlation indicates a positive association between increased engagement and weight loss).
cIncludes self-weighing.
dCP: cell phone.
ePC: personal coaching.
fGroup sessions only occur in the first 2 months.
Our results demonstrate that engagement in mHealth delivery of a behavioral weight loss intervention was associated with weight loss. Our findings suggest that the more the participants used the smartphone app or self-weighed, the more weight loss was observed during the first 6 months of the study for both intervention arms. This association continued to be true for the PC arm into months 7 to 12, but not for the CP arm. Despite the fundamental differences in the time and effort needed in using various components of the smartphone app or in completing personal contacts (ie, group sessions and monthly calls), the finding is consistent—engagement with the intervention is associated with weight loss. It is unclear, however, what level of engagement is required for effective weight loss, and if a different level of engagement is effective for weight loss maintenance.
Our findings are consistent with previous research showing that greater engagement with an intervention was associated with greater weight loss, even with different types of engagement measures [
Unlike self-weighing, other components of self-monitoring components such as dietary tracking were only used during the first month and almost never used beyond the first month. This low engagement in dietary tracking may result from low motivation [
Indeed, ours and other studies have shown that the engagement dropped drastically, even after the first month, and declined continuously over time [
In a 12-month behavioral weight loss study, the self-monitoring pattern of 148 participants also varied and declined over time [
Although traditional personal contact has been perceived as the ideal mode of intervention delivery, in this study, completion of the group sessions alone or combined with monthly calls in the PC arm was not significantly associated with weight change. However, engagement as assessed by overall app use or self-weighing was significantly associated with weight loss, even for the PC arm that received regular and sustained personal support. This finding suggests that mHealth for behavioral interventions could supplement and even enhance interventions based on personal contact, even in the setting of a reduced engagement pattern. Combining mHealth intervention with human support may be more efficient than using either of them alone. This is consistent with a recent study that randomized 102 participants into 3 weight loss intervention arms versus control for 12 weeks: a personal contact arm, an mHealth app-only arm, and a combined arm with personal contact and an mHealth app. The authors reported that the combined personal contact and mHealth app arm was as effective as the personal contact arm and tended to be more effective than the mHealth app arm [
Our data suggest that prompting may be helpful to generate engagement to some degree because the CP arm that received prompting regularly used the smartphone app components more than the PC arm did across all measures of engagement. A meta-analysis of 14 studies with varying designs showed that technology-based prompting had a small to moderate effect on engagement as compared with no-strategy [
This study has several strengths. The engagement data reported here were collected objectively with a smartphone app, and the main outcome of weight was reliably measured at each of the study visits in the clinic and does not rely on self-reporting. Furthermore, this study generated a relatively large amount of engagement data of young adults (n=242) for an extended period (24 months). Another strength of this study is the ability to collect engagement data with each of the cell phone app’s components and with the personal interactions, where the design of the intervention components was based on behavioral theories and prior research evidence.
The study has several limitations that must be considered when interpreting data. Regardless of the reason for joining the CITY study, the varying motivation for weight loss among the participants may have contributed to the varying level of engagement in the intervention arms. Increasing motivation may increase engagement and subsequent weight loss; however, identifying effective level of engagement may also be important for all weight loss studies and programs. Another weakness of the study is that limited study resources prevented development of an intervention app as attractive, polished, and robust as some commercial apps, which could have an impact on engagement. Unfortunately, it was beyond the scope of this study to tease apart whether the reduction in engagement over time may have been due to lack of motivation or challenges with the app design and other technical reasons. Our study compensation for smartphone data coverage, which was offered to both the PC and CP arms, may have incentivized participants to stay in the study but would not contribute to the differences in engagement between the 2 arms. This compensation would not be available to app users if the app were widely deployed. Our compensation, however, did not require any substantial level of engagement or use of app components, and so, participants with low motivation who may have otherwise dropped out of the study may have continued until the end. The overall engagement was lower than expected and desired, but the pattern was consistent with other studies. Messages and tips to encourage healthy lifestyle and weight loss management were delivered through the app home screen, but the smartphone’s operating system prevented the measurement of whether participants covered them up with other app icons or even turned off the messages altogether; this behavior would affect engagement. The fact that engagement dropped substantially early suggests that a more effective intervention that automatically adapts to behavior and self-measured engagement, such as using just-in-time adaptive design, may be needed [
In this study, engagement assessed using different measures was associated with weight loss. Nevertheless, engagement declined over time at varying rates for different intervention engagement components. This study suggests that a variety of strategies may be needed during different stages of an intervention to increase and sustain engagement required for intervention effectiveness. Self-weighing was associated with weight loss regardless of the baseline characteristics of the participants, suggesting that an effective weight loss program may not need to include multiple behavioral strategies. Focusing on a single effective strategy in conjunction with prompting may be better than offering more components that most participants may not use. Future studies should clarify the definition of effective engagement. In addition, future studies should explore the motivations for participant engagement and nonengagement to design effective strategies for addressing those specific challenges.
Description of the major components of the Cell Phone Intervention For You app, the user actions within each component that count toward engagement, and the prompting frequency for selected components.
Baseline characteristics of cell phone participants by quartile of mean number of apps used per day (including self-weighing) in the first 6 months.
Baseline characteristics of personal coaching participants by quartile of mean number of app uses per day (including self-weighing) in the first 6 months.
CONSORT‐EHEALTH checklist (V 1.6.1).
analysis of variance
body mass index
Cell Phone Intervention For You
cell phone
interactive voice response
mobile health
National Heart Lung and Blood Institute
personal coaching
The authors acknowledge funding from the National Institute of Health (1U01 HL096720-01) and the Veterans Affairs Health Services Research and Development Service Career Scientist Award (RCS 14-443).
All authors contributed to the design, conduct, and analysis of the CITY study results. All authors also contributed to the preparation of the manuscript, and they reviewed and approved the manuscript.
SG currently receives consulting fees from Gilead Sciences for serving on multiple Data Monitoring Committees. Although the relationship is not perceived to represent a conflict with this work, it has been included in the spirit of full disclosure. GGB holds equity in Coeus Health and serves on the scientific advisory board of Nutrisystem. These organizations had no role in study design, data collection, data analysis and interpretation of data, in the writing of the report, or in the decision to submit the article for publication.