This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mhealth and uhealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.
Effective treatment of obesity in children and adolescents traditionally requires frequent in-person contact, and it is often limited by low participant engagement. Mobile health tools may offer alternative models that enhance participant engagement.
The aim of this study was to assess child engagement over time, with a mobile app–based health coaching and behavior change program for weight management, and to examine the association between engagement and change in weight status.
This was a retrospective cohort study of user data from
A total of 1120 participants were included in analyses. At baseline, participants had a mean age of 12 years (SD 2.5), mean BMI percentile of 96.6 (SD 3.1), mean %BMIp95 of 114.5 (SD 16.5), and they were predominantly female 68.04% (762/1120). Participant distribution across commitment periods was 26.07% (292/1120) for 4 weeks, 61.61% (690/1120) for 12-16 weeks, and 12.32% (138/1120) for 24 weeks. The median coaching sessions (interquartile range) received were 8 (3-16) for the 4-week group, 9 (5-12) for the 12- to 16-week group, and 19 (11-25) for the 24-week group (
Among overweight and obese children using a mobile app–based health coaching and behavior change program, increased engagement was associated with longer voluntary commitment periods, and increased number of coaching sessions was associated with decreased weight status.
A total of 1 in 3 children in the United States is either overweight or obese [
Among obesity treatment trials for adults, mHealth tools appear to successfully assist patients in managing comorbidities, such as diabetes, improve physical activity and dietary behaviors, and achieve meaningful weight loss [
In this study, we aimed to assess the engagement of overweight or obese children with a commercially available mHealth tool (
This was a retrospective cohort study of participants in a commercial, mobile app–based platform and program (
The
Mobile app platform.
The self-monitoring component of the program employs the BCTs of self-monitoring of behavior and monitoring of outcomes of behavior [
The individualized coaching sessions component is provided by individuals who are hired and trained as coaches by
In addition to coaching sessions, participants are also able to contact their coach between coaching sessions, via short message service text messages, email, or in-app messaging. Independent of the
The study examined a retrospectively identified cohort of participants who initially utilized the
The inclusion criterion (
Cohort flow diagram.
The exclusion criteria (
Study participants were voluntarily subscribed or assigned to 1 of 3 commitment periods: 4 weeks, 12 to 16 weeks, or 24 weeks. Each participant was supported by either an employer-benefited plan, a health insurer–benefited plan, or a self-paid plan. The cost of the program is covered by either the parent (self-pay), a parent’s employer, or a family health insurance plan. Self-pay rates are dependent on the commitment period. Participants in self-paid plans voluntarily chose from 1 of 3 commitment periods: 4 weeks, 12 weeks, or 24 weeks. Those in employer- or health insurer–benefited plans were contractually assigned to 1 of 2 commitment periods: 12 weeks or 16 weeks. Of note, there were only 16 participants in the 16-week commitment period, and for analytic purposes, these participants were combined with the 12-week period to form a 12- to 16-week commitment period group. All participants had the ability to renew or change their plan at the end of the initial commitment period; however, data regarding renewals or changes were not available for analysis.
Participant demographic characteristics were limited to self-reported age and sex, provided by either child or parent. Age in years at baseline was used to create 4 distinct age group categories. The age group categories were defined as 5 to 11, 12 to 14, and 15 to 18 years old. These age groups were informed by commonly reported groupings from population prevalence and large intervention studies [
The primary outcome and measure of participant engagement was
Other measures of participant engagement included participation period, program retention, coaching messages, dietary events, and physical-activity events.
A secondary outcome of the study was change in the participant’s weight status, defined as the
Descriptive statistics were used to compare baseline characteristics (age, age group, sex, BMI percentile, %BMIp95, weight category, obesity class, and payment source), primary outcome (participant engagement), and secondary outcome (change in weight status) across the 3 commitment periods. Categorical variables were expressed as absolute values and corresponding percentages. Normally distributed continuous variables are reported as a mean with standard deviation (SD). The continuous engagement measures analyzed had nonnormal distribution patterns, each of these are reported as a median with interquartile range (IQR). Differences of measures across commitment period groups were explored using Chi-square tests for categorical variables and analysis of variance for normally distributed continuous measures. Similarly, differences across commitment periods for nonparametric continuous measures were analyzed using Kruskal-Wallis tests. Significance of change in weight status within commitment periods was analyzed using paired two-tailed
Multivariable linear regression models were constructed to examine 2 sets of associations: (1) between the primary outcome (number of coaching sessions) and each commitment period (reference of 24-week period) and (2) between the primary outcome (number of coaching sessions) and the secondary outcome (change in %BMIp95). Each multivariable model included adjustment for significant baseline differences in age group and sex. A sensitivity analysis, excluding involuntary participants (ie, health plan or employer supported), was performed to isolate differences associated with voluntariness of commitment period (
Of the 3242 participants assessed for eligibility, 1579 met the inclusion criteria. Of those, 305 participants were excluded for being outside the age range, normal weight at baseline (79), missing baseline data (46), or data measurement error. This yielded a final analytic sample of 1120 study participants, displayed in (
The baseline characteristics for the study sample by commitment period are displayed in (
Baseline participant characteristics by commitment period.
Baseline characteristics | All periods (N=1120) | 4 weeks (n=292) | 12-16 weeksa (n=690) | 24 weeks (n=138) | ||
Age (years), mean (SD) | 12.0 (2.5) | 11.9 (2.2) | 12.0 (2.7) | 12.0 (2.4) | .89b | |
|
.61c | |||||
|
5-11 years | 573 (51.16) | 150 (51.4) | 350 (50.7) | 73 (52.9) |
|
|
12-14 years | 392 (35.00) | 109 (37.3) | 237 (34.4) | 46 (33.3) |
|
|
15-18 years | 155 (13.84) | 33 (11.3) | 103 (14.9) | 19 (13.8) |
|
|
.20c | |||||
|
Male | 358 (31.96) | 103 (35.3) | 218 (31.6) | 37 (26.8) |
|
|
Female | 762 (68.04) | 189 (64.7) | 472 (64.1) | 101 (73.2) |
|
Body mass index percentile, mean (SD) | 96.6 (3.1) | 96.4 (3.3) | 96.5 (3.1) | 97.3 (2.5) | .009b | |
%BMIp95d, mean (SD) | 114.5 (16.5) | 113.4 (17.5) | 114.1 (19.3) | 118.8 (19.3) | .01b | |
|
.03c | |||||
|
Overweight | 262 (23.39) | 74 (25.3) | 168 (24.4) | 20 (14.5) |
|
|
Obese | 858 (76.61) | 218 (74.7) | 522 (75.7) | 118 (85.5) |
|
|
.39c | |||||
|
Class I | 508 (59.21) | 128 (58.7) | 315 (60.3) | 65 (55.1) |
|
|
Class II | 236 (27.51) | 65 (29.8) | 140 (26.8) | 31 (26.3) |
|
|
Class III | 114 (13.29) | 25 (11.5) | 67 (12.8) | 22 (18.6) |
|
|
<.001c | |||||
|
Self-pay | 743 (66.34) | 292 (100) | 314 (45.5) | 138 (100) |
|
|
Health plan | 278 (24.82) | —h | 278 (40.3) | — |
|
|
Employer | 99 (8.84) | — | 99 (14.3) | — |
|
a12 to 16 weeks includes n=674 participants with 12-week and n=16 participants with 16-week commitment periods.
bAnalysis of variance.
cChi-square test.
d%BMIp95: percentage of the 95th BMI percentile.
eCategories by Centers for Disease Control and Prevention body mass index percentile for Age and Sex. Overweight (BMI Percentile ≥85 and <95th), Obese (BMI Percentile ≥95th).
fObesity Class I (≥95th to <120 %BMIp95), Class II (≥120 to <140 %BMIp95, or BMI ≥35), Class III (≥140 %BMIp95, or BMI ≥40), inclusive of N 858 participants categorized as obese.
gThe 4 weeks and 24 weeks commitment periods consisted entirely of Self-pay participants, accordingly data for Health plan and Employer are not applicable.
hNot applicable.
The engagement of participants with the mobile app program, compared across commitment periods, is displayed in (
The primary outcome of median number of coaching sessions received was 8 (IQR 3-15) for the 4-week group, 9 (IQR 5-12) for the 12- to 16-week group, and 19 (IQR 11-25) for the 24-week group (
Engagement of participants with mobile app–based program by commitment period, among all participants (N=1120).
Engagement measures | All periods (N=1120) | 4 weeks (n=292) | 12-16 weeksa (n=690) | 24 weeks (n=138) | |
Coaching sessionsb, median (IQRc) | 9 (5-15) | 8 (3-16) | 9 (5-12) | 19 (11-25) | <.001d |
Coaching messagese, median (IQR) | 3 (0-10) | 4 (0-11) | 3 (0-9) | 6 (1-14) | <.001d |
Dietary eventsf, median (IQR) | 174 (83-325) | 163 (80-321) | 153 (76-278) | 335 (188-596) | <.001d |
Physical activity eventsg, median (IQR) | 42 (15-91) | 42 (15-98) | 36 (13-78) | 76 (33-152) | <.001d |
Participation periodh, median (IQR) | 15 (12-30) | 16 (8-36) | 14 (12-22) | 30 (22-51) | <.001d |
Program retentioni, n (%) | 895 (79.91) | 270 (92.5) | 530 (76.8) | 95 (68.8) | <.001j |
aIncludes 674 participants with 12-week and 16 participants with 16-week commitment periods.
bMedian of total number of coaching sessions between participant and coach.
cIQR: interquartile range.
dKruskal-Wallis Test.
eMedian of total number of text messages from participant to coach.
fMedian of total number of dietary event food logs recorded by participants (n=1100), otherwise missing.
gMedian of total number of physical activity event logs recorded by participants (n=1078), otherwise missing.
hMedian of total weeks between sign up and last recorded interaction with the app.
iProportion of participants who completed equal or greater weeks than initial commitment period.
jChi-square test.
Engagement of participants with mobile app–based program by age group, among all participants (N=1120).
Engagement measures | All age groups, (N=1120) | 5-11 years (n=573) | 12-14 years (n=392) | 15-18 years (n=155) | |
Coaching sessionsa, median (IQRb) | 9 (5-15) | 10 (5-15) | 9 (5-14) | 10 (6-15) | .77c |
Coaching messagesd, median (IQR) | 3 (0-10) | 3 (0-10) | 3 (0-12) | 3 (0-10) | .94c |
Dietary eventse, median (IQR) | 174 (83-325) | 171 (80-318) | 175 (84-330) | 177 (87-342) | .68c |
Physical activity eventsf, median (IQR) | 42 (15-91) | 44 (15-89) | 41 (15-92) | 36 (13-102) | .89c |
Participation periodg, median (IQR) | 15 (12-30) | 15 (12-32) | 15 (11-27) | 14 (12-27) | .33c |
Program retentionh, n (%) | 895 (79.91) | 493(79.1) | 314 (80.1) | 128 (82.6) | .62i |
aMedian of total number of coaching sessions between participant and coach.
bIQR: interquartile range.
cKruskal-Wallis Test.
dMedian of total number of text messages from participant to coach.
eMedian of total number of dietary event food logs recorded by participants (n=1100), otherwise missing.
fMedian of total number of physical activity event logs recorded by participants (n=1078), otherwise missing.
gMedian of total weeks between sign-up and last recorded interaction with the app.
hProportion of participants who completed equal or greater weeks than initial commitment period.
iChi-square test.
Results of unadjusted and adjusted models for the primary outcome (number of coaching sessions per participant) are displayed in
Factors associated with total number of coaching sessions, among all participants (N=1120).
Participant factors | Unadjusteda beta-coefficient (95% CI) | Adjustedb beta-coefficient (95% CI) | |||
|
|||||
|
Age 5-11 years (reference: 15-18 years) | –0.17 (–2.14 to 1.79) | .86 | –0.13 (–2.03 to 1.78) | .89 |
|
Age 12-14 years (reference: 15-18 years) | –0.59 (–2.68 to 1.44) | .56 | –0.53 (–2.53 to 1.46) | .59 |
|
|||||
|
Male (reference: female) | –1.38 (–2.77 to 0.01) | .05 | –1.15 (–2.50 to 0.19) | .09 |
|
|||||
|
4 weeks (reference: 24 weeks) | –8.15 (–10.31 to –5.98) | <.001 | –8.03 (–10.19 to –5.87) | <.001 |
|
12-16 weeks (reference: 24 weeks) | –9.41 (–11.36 to –7.46) | <.001 | –9.34 (–11.30 to –7.39) | <.001 |
aUnadjusted bivariate linear regression model of coaching sessions outcome as a function of age group, sex, or commitment period.
bAdjusted multivariable linear regression model of coaching sessions outcome adjusted as a function of age group, sex, and commitment period.
Within each commitment period, the mean change between baseline and endpoint for %BMIp95 was –5.4 (95% CI –6.2 to –4.5) for 4 weeks (
This retrospective study described the engagement of a large cohort of children and adolescents, with a multicomponent mobile app–based comprehensive behavioral program aimed at promoting healthy dietary and exercise lifestyle behaviors. Unlike traditional behavioral interventions and clinical weight management programs, which largely rely on in-person visits and sessions [
Our findings of overall engagement with a median of 9 (IQR 5-15) coaching sessions during the participation period is notable for an mHealth program. This level of engagement, although considered low intensity by USPSTF criteria, is comparable with contact levels of in-person weight management programs [
Finally, in this observational study, we found a significant association between the number of coaching sessions and the change in self-reported weight status during participation in the program. This association suggests that greater exposure to coaching sessions in this study was correlated with increased weight reduction. USPSTF analyses of intensive in-person interventions suggest a dose-response relationship between intervention hours received and beneficial changes in weight, with effective programs requiring at least 26 contact hours [
The study has limitations common to other studies of digital health and mHealth interventions [
Still, rigorous and independent studies of digital health and mHealth interventions are limited, and this study meaningfully contributes to the literature on digital health and mHealth interventions focused on obesity treatment and prevention. First, the intervention was comprehensively designed with multiple components that have been shown to be effective strategies for weight management and behavior change in pediatric populations [
Our findings have implications for clinical care, population health, and public policy. Clinicians providing obesity treatment may consider the incorporation of mHealth programs, such as the one studied here, as an adjunct to clinic visits and traditional medical management strategies. Health care systems aiming to improve population health management efforts might find these types of mHealth solutions more accessible for providing access to care for patients in rural areas where availability of providers may be limited or to patients in urban areas, who may be restricted by long commute times or have limited transportation options. Finally, public health leaders and policy makers may be encouraged by the role that emerging digital technologies could play in addressing obesity at the community level.
This study of a mobile app–based health behavior change and health coaching program among a large cohort of overweight and obese participants demonstrated high participant engagement. Increased engagement with coaching sessions was associated with longer voluntary commitment periods. Overall program retention was higher than that reported for similar in-person intensive behavioral interventions and weight management programs. Participant engagement with coaching sessions was associated with decreases in weight status (%BMIp95). Taken together, these findings highlight the potential of mHealth platforms as a promising model for delivering behavioral interventions that support weight management and behavior change for overweight or obese children and adolescents.
Supplementary tables – Baseline participant characteristics by age group, all participants (N=1120) and Factors associated with total number of coaching sessions, among self-pay (voluntary) participants (N=743).
BMI as percentage of the 95th percentile
behavior change technique
body mass index
Centers for Disease Control and Prevention
Child Health Research Institute
Health Resources and Services Administration
interquartile range
Lucile Packard Children’s Hospital
mobile health
US Preventive Services Task Force
VC was affiliated with the Division of General Pediatrics, Department of Pediatrics at Stanford University School of Medicine at the time this study was conducted, and is currently affiliated with Rutgers New Jersey Medical School Division of General Internal Medicine, Department of Medicine. VC conducted this study with support from Stanford’s Health Resources and Services Administration (HRSA) Hispanic Center of Excellence Grant (D34HP16047) as well as the Stanford Child Health Research Institute (CHRI) and Lucile Packard Children’s Hospital (LPCH) Stanford. The contents of this publication represent the views of the authors and do not necessarily reflect the views of HRSA, CHRI, or LPCH. The authors thank
None declared.