Design, Implementation, and Examination of a Remote Patient Monitoring System for Pediatric Obesity: Protocol for an Open Trial Pilot Study
Bibliographic record
Abstract
BACKGROUND: Pediatric obesity is a critical public health issue. Augmenting care in multidisciplinary pediatric obesity clinics with innovative evidence-based technology to improve weight status and health outcomes is needed. OBJECTIVE: This study describes the design and methods of an open trial pilot study to examine a remote patient monitoring system (RPMS) for children aged 8-17 years who are receiving treatment in a multidisciplinary pediatric obesity clinic. METHODS: Participants will include 45 youth with obesity and their parents. Families will receive standard care in the clinic and the RPMS for 3 months. The RPMS consists of a tablet, weight scale, and pedometer. The system provides daily educational content and involves the use of the pedometer and weekly weigh-ins. Children and parents will complete baseline, posttreatment (month 3), and follow-up assessments (month 6). The primary aim of the study is to examine feasibility and satisfaction with the RPMS and assess its initial effectiveness. RESULTS: We hypothesize high feasibility and satisfaction, with rates over 75%. Furthermore, after RPMS treatment, children will exhibit improved weight status, health outcomes, dietary intake, physical activity, health-related quality of life, self-efficacy, and home-food environment compared to before treatment. These gains are expected to persist at follow-up. CONCLUSIONS: This study is novel in that it is the first to design, implement, and examine an RPMS in a pediatric obesity clinic. If the RPMS is feasible, effective, and easily accessible, it may prove to be a practical, acceptable, and cost-effective weight management treatment for youth seeking treatment for severe obesity. TRIAL REGISTRATION: ClinicalTrials.gov NCT04029597; https://clinicaltrials.gov/ct2/show/NCT04029597. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/29858.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.073 | 0.060 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.054 | 0.011 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".