Modest treatment effects and high program attrition: The impact of interdisciplinary, individualized care for managing paediatric obesity
Bibliographic record
Abstract
BACKGROUND: There is an urgent need to identify effective weight management interventions in real-world, clinical settings to improve the health of children with obesity. OBJECTIVES: To determine the impact of individualized, interdisciplinary care on the weight status of children with obesity; to assess the relationship between clinical interactions and change in participants' weight status; and to document the degree of program attrition. METHODS: A retrospective medical record review of clinical and administrative data from a paediatric weight management clinic in Edmonton, Alberta, was performed, which included data from a group of five- to 18-year-olds (body mass index [BMI] ≥85th percentile) collected from 2008 to 2012. Demographic, anthropometric and attendance data were retrieved from baseline and follow-up at three-, seven- and 11-month timepoints. The primary outcomes were participants' BMI z-score and change in BMI z-score over time. RESULTS: Data from 165 individuals were included. Among those with follow-up anthropometric data, weight stabilization occurred at three (n=127) and seven months (n=84). For individuals with follow-up anthropometric data at 11 months (n=44), BMI z-score tended to decrease over time (-0.05±0.12 units; P=0.06). Program attrition increased over time (23%, 49% and 73% at three-, seven- and 11-month follow-ups, respectively). Between presentation and three-month follow-up, there was an inverse relationship between the number of clinical appointments attended and change in BMI z-score (r= -0.18; P=0.04), an association that became nonsignificant at seven and 11 months (both P>0.05). CONCLUSION: An individualized, interdisciplinary weight management intervention led to weight stabilization and a modest weight reduction in children with obesity. Strategies to minimize program attrition are needed to optimize family engagement in care and success in managing paediatric obesity.
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 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 | 0.031 | 0.073 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".