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Record W2968488983 · doi:10.2196/14458

Impact of a Mobile App–Based Health Coaching and Behavior Change Program on Participant Engagement and Weight Status of Overweight and Obese Children: Retrospective Cohort Study

2019· article· en· W2968488983 on OpenAlexvenueno aff
Victor Cueto, C. Jason Wang, Lee Sanders

Bibliographic record

VenueJMIR mhealth and uhealth · 2019
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
Fundersnot available
KeywordsOverweightHealth coachingCoachingBody mass indexPercentileMedicinemHealthCohortBehavior changeWeight managementCohort studyGerontologyPsychologyPhysical therapyPsychological interventionPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: 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. OBJECTIVE: 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. METHODS: This was a retrospective cohort study of user data from Kurbo, a commercial program that provides weekly individual coaching via video chat and supports self-monitoring of health behaviors through a mobile app. Study participants included users of Kurbo between March 2015 and March 2017, who were 5 to 18 years old and who were overweight or obese (body mass index; BMI ≥ 85th percentile or ≥ 95th percentile) at baseline. The primary outcome, engagement, was defined as the total number of health coaching sessions received. The secondary outcome was change in weight status, defined as the change in BMI as a percentage of the 95th percentile (%BMIp95). Analyses of outcome measures were compared across three initial commitment period groups: 4 weeks, 12 to 16 weeks, or 24 weeks. Multivariable linear regression models were constructed to adjust outcomes for the independent variables of sex, age group (5-11 years, 12-14 years, and 15-18 years), and commitment period. A sensitivity analysis was conducted, excluding a subset of participants involuntarily assigned to the 12- to 16-week commitment period by an employer or health plan. RESULTS: 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 (P<.001). Adjusted for sex and age group, participants in the 4- and 12-week groups participated in -8.03 (95% CI -10.19 to -5.87) and -9.34 (95% CI -11.31 to -7.39) fewer coaching sessions, compared with those in the 24-week group (P<.001). Adjusted for commitment period, sex, and age group, the overall mean change in %BMIp95 was -0.21 (95% CI -0.25 to -0.17) per additional coaching session (P<.001). CONCLUSIONS: 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.097
GPT teacher head0.484
Teacher spread0.387 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations51
Published2019
Admission routes1
Has abstractyes

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