Brief Primary Care Obesity Interventions: A Meta-analysis
Bibliographic record
Abstract
CONTEXT: Although practice guidelines suggest that primary care providers working with children and adolescents incorporate BMI surveillance and counseling into routine practice, the evidence base for this practice is unclear. OBJECTIVE: To determine the effect of brief, primary care interventions for pediatric weight management on BMI. DATA SOURCES: Medline, CENTRAL, Embase, PsycInfo, and CINAHL were searched for relevant publications from January 1976 to March 2016 and cross-referenced with published studies. STUDY SELECTION: Eligible studies were randomized controlled trials and quasi-experimental studies that compared the effect of office-based primary care weight management interventions to any control intervention on percent BMI or BMI z scores in children aged 2 to 18 years. DATA EXTRACTION: Two reviewers independently screened sources, extracted data on participant, intervention, and study characteristics, z-BMI/percent BMI, harms, and study quality using the Cochrane and Newcastle-Ottawa risk of bias tools. RESULTS: A random effects model was used to pool the effect size across eligible 10 randomized controlled trials and 2 quasi-experimental studies. Compared with usual care or control treatment, brief interventions feasible for primary care were associated with a significant but small reduction in BMI z score (-0.04, [95% confidence interval, -0.08 to -0.01]; P = .02) and a nonsignificant effect on body satisfaction (standardized mean difference 0.00, [95% confidence interval, -0.21 to 0.22]; P = .98). LIMITATIONS: Studies had methodological limitations, follow-up was brief, and adverse effects were not commonly measured. CONCLUSIONS: BMI surveillance and counseling has a marginal effect on BMI, highlighting the need for revised practice guidelines and the development of novel approaches for providers to address this problem.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.010 |
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; both teacher heads agree on what is shown here.
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".