Attrition from paediatric weight management impacts anthropometric outcomes at 2 years, but not health‐related quality of life
Bibliographic record
Abstract
The study objective is to evaluate the influence of attrition from a paediatric weight management program (PWM) on health indicators over a 2-year period. In this observational study, children and youth with obesity were recruited at entry into a family-based behaviour modification PWM and had four research study visits, independent of clinic visits, over 2 years. Participants were divided into attrition groups based on length of clinic enrolment. Body composition, cardiometabolic health and health-related quality of life (HRQoL) were assessed. Among 269 children enrolled, 19% had no clinic treatment visit, 16% had treatment visits only up to 6 months, 23% up to 1 year and 42% had at least one clinic visit after 1 year (No Attrition). Greater declines in BMI z-score and body fat were seen at 2 years in children with No Attrition, while improvements in HRQoL were similar for all attrition groups. Children who attended at least one treatment visit reported improved HRQoL up to 2 years, regardless of duration in clinic. In contrast, declines in body fat and BMI z-score were greater at 2 years for those with at least one visit after 1 year. Continued efforts to reduce attrition are likely to improve anthropometric health outcomes during PWM.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".