Impact of cognitive-behavioral interventions on weight loss and psychological outcomes: A meta-analysis.
Bibliographic record
Abstract
OBJECTIVES: To examine the effects of cognitive-behavioral therapy weight loss (CBTWL) interventions on weight loss, psychological outcomes (eating behaviors [cognitive restraint, emotional/binge eating], and depressive/anxiety symptoms) in adults with overweight or obesity. METHODS: To be included, studies had to (a) be randomized controlled clinical trials of a CBTWL intervention versus a comparison intervention; (b) include weight loss and psychological outcomes; and (c) include patients who were at least overweight to obese. This review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement (Moher, Liberati, Tetzlaff, & Altman & the PRISMA Group, 2009). RESULTS: Twelve studies (6,805 participants) were included. The average weight loss difference between arms was -1.70 kg (95% confidence interval [CI]: -2.52 to -0.86, I2 = 1%) in favor of CBTWL. The standardized mean difference on cognitive restraint was 0.72 (95% CI: 0.33 to 1.09; I2 = 81%) and -0.32 (95% CI: -0.49 to -0.16; I2 = 0%) for emotional eating in favor of CBTWL. The reduction in depressive symptoms was not statistically different between the groups (-0.10 [95% CI: 0.21 to 0.02], I2 = 36%). Meta-analyses were not possible for anxiety and binge eating. CONCLUSIONS: In addition to weight loss, current evidence suggests that CBTWL is an efficacious therapy for increasing cognitive restraint and reducing emotional eating. However, CBTWL does not seem to be superior to other interventions for decreasing depressive symptoms. Future studies should focus on understanding how psychological factors impact weight loss and management. (PsycINFO Database Record
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.045 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".