Mental health and socioeconomic status impact adherence to youth activity and dietary programs: a meta-analysis
Bibliographic record
Abstract
PURPOSE: Substantial efforts have gone into reducing the physiological and psychological harm of obesity in youth, but few studies have reviewed the factors contributing to adherence to pediatric weight management programs. The attrition rates to programs offering multiple components to address BMI improvement and healthy lifestyle change among youth are quite high. The purpose of this study is to review the literature for factors contributing to adherence to these programs among children and youth with obesity and determine pooled effect of these factors. METHODS: A systematic literature search and meta-analysis was conducted through the PubMed database on pediatric weight management interventions offering at least physical activity and dietary support for obese youth aged 10-17 years, where variables contributing to adherence were reported. Only those studies achieving a threshold of methodological rigour were included. RESULTS: Altogether, seven studies were included in the analysis. There was a pooled RR of lower socioeconomic status on non-adherence of 1.34 [95% confidence intervals 1.19-1.52] and poorer mental health on non-adherence of 1.12 [95% confidence intervals 1.08-1.17]. CONCLUSION: It is important to address barriers related to lower socioeconomic status in pediatric weight management programs to increase adherence. Further, addressing supports for those with poorer mental health can reduce the risk of non-adherence in multi-disciplinary programs targeting youth with obesity.
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.046 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".