A Pilot Lifestyle Intervention to Support Adolescent Metabolic and Bariatric Surgery Completers: Feasibility and Exploratory Outcomes (Preprint)
Bibliographic record
Abstract
BACKGROUND Metabolic and bariatric surgery (MBS) is a safe and effective treatment for adolescents with severe obesity, yet no standardized lifestyle interventions exist to support sustained behavior change post-MBS. OBJECTIVE This pilot study assessed the feasibility and acceptability of TeenLyft, an online lifestyle support program for adolescents undergoing MBS, and explored preliminary clinical and safety outcomes to inform the design of a future randomized trial. METHODS Adolescents aged 12–18 years were recruited from a tertiary care MBS center and enrolled in TeenLyft. The study was not powered or designed as a randomized controlled trial but rather as a pilot to guide future RCT development. Feasibility domains included recruitment, retention, data completeness, intervention fidelity, and engagement, with predefined progression criteria of ≥80% enrollment, ≥70% retention, ≥75% data completeness, and ≥90% fidelity. Exploratory clinical and safety measures (weight, BMI, and cardiometabolic markers) were collected descriptively to confirm that participation was not associated with harm. RESULTS Twenty-nine adolescents (mean age 15.9 years; 75.9% female; 44.8% Hispanic; mean BMI 47.8 kg/m²) were enrolled, representing 145% of the recruitment target (n=20), with 72% retention at six months. All feasibility progression criteria were met. Descriptive trends showed expected post-MBS reductions in weight and BMI and improvements in blood pressure and HbA1c, with no adverse cardiometabolic effects observed. CONCLUSIONS TeenLyft demonstrated high feasibility, acceptability, and safety as an adjunct to adolescent MBS care. Findings support progression to a fully powered randomized trial to evaluate long-term effectiveness and sustainability. CLINICALTRIAL ClinicalTrials.gov, NCT05393570; Registered on May 16, 2022.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".