The efficacy of cognitive behavioral therapies for depression in China in comparison with the rest of the world: A systematic review and meta-analysis.
Bibliographic record
Abstract
OBJECTIVE: There is consistent evidence that cognitive behavioral therapies (CBTs) are effective interventions for adult depression. While some evidence has compared these effects in different countries, no prior systematic review and meta-analysis has compared the efficacy of CBTs between Chinese and people from the rest of the world. The current meta-analysis addressed this gap by a systematic review of eligible studies from Chinese and worldwide databases. METHOD: Hedges' g was calculated using a random-effects model. Subgroup analyses and multilevel meta-analytic models were conducted to examine the relationship among effect sizes and the characteristics in Chinese studies. Metaregression analyses were conducted to explore the difference of the efficacy of CBTs between Chinese studies and non-Chinese studies after controlling for the moderators. RESULTS: = .011). CONCLUSIONS: CBTs are effective interventions for adult depression and deserve more attention in China for depression management. Moderators related to study design, clinical features, and cultural factors need to be considered in the interpretation of the results. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.017 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".