Acceptance and commitment therapy versus cognitive behavioral therapy for insomnia: A randomized controlled trial.
Bibliographic record
Abstract
OBJECTIVE: To compare the effectiveness of an acceptance and commitment therapy (ACT)-based protocol and cognitive behavior therapy (CBT) for insomnia in adults. METHOD: The participants comprised 227 adults with insomnia. They were randomized to six weekly group sessions consisting of acceptance and commitment therapy for insomnia (n = 76), cognitive behavioral therapy for insomnia (n = 76), or waitlist (WL; n = 75). RESULTS: Both treatment modalities significantly reduced insomnia severity with large effect sizes in the posttreatment phase. These results were maintained during the follow-up period with large effect sizes. CBT was superior to ACT in reducing the Insomnia Severity Index at posttreatment and follow-up, with a small effect size. ACT was superior to WL at posttreatment and at follow-up, with a moderate effect size. The treatment response and remission ratios were higher with CBT at posttreatment and similar at 6-month follow-up for both therapies, as ACT made further gains in response and remission. ACT had a significantly higher proportion of response and remission than WL in both periods (posttreatment and follow-up). Both therapies improved daytime functioning at both posttreatment and follow-up, with few differential changes across the groups. CONCLUSIONS: Both cognitive behavior therapy and acceptance and commitment therapy are effective, with CBT showing superiority and ACT showing delayed improvement. ACT has proven to be an effective therapy, especially in the long term, even in the absence of behavioral techniques such as stimulus control and sleep restriction, and it is a viable option for those who have difficulties adhering to behavioral techniques. (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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".