Weight-loss intervention adherence and factors promoting adherence: a meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Adhering to weight loss interventions is difficult for many people. The majority of those who are overweight or obese and attempt to lose weight are simply not successful. The objectives of this study were 1) to quantify overall adherence rates for various weight loss interventions and 2) to provide pooled estimates for factors associated with improved adherence to weight loss interventions. METHODS: We performed a systematic literature review and meta-analysis of all studies published between January 2004 and August 2015 that reviewed weight loss intervention adherence. RESULTS: After applying inclusion and exclusion criteria and checking the methodological quality, 27 studies were included in the meta-analysis. The overall adherence rate was 60.5% (95% confidence interval [CI] 53.6-67.2). The following three main variables were found to impact adherence: 1) supervised attendance programs had higher adherence rates than those with no supervision (rate ratio [RR] 1.65; 95% CI 1.54-1.77); 2) interventions that offered social support had higher adherence than those without social support (RR 1.29; 95% CI 1.24-1.34); and 3) dietary intervention alone had higher adherence than exercise programs alone (RR 1.27; 95% CI 1.19-1.35). CONCLUSION: A substantial proportion of people do not adhere to weight loss interventions. Programs supervising attendance, offering social support, and focusing on dietary modification have better adherence than interventions not supervising attendance, not offering social support, and focusing exclusively on exercise.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it