Cognitive behavioral therapy for perinatal anxiety: A randomized controlled trial
Bibliographic record
Abstract
Background: Up to one in five women meet diagnostic criteria for an anxiety disorder during the perinatal period (i.e. pregnancy and up to 1 year postpartum). While psychotropic medications are effective, they are associated with risks for mothers and babies. There is a growing demand for evidence-based non-pharmacological treatments for perinatal anxiety. Objective: To evaluate the effectiveness of a cognitive behavioral group therapy protocol for perinatal anxiety. Methods: In total, 96 women were randomized to cognitive behavioral group therapy or waitlist at a clinic specializing in women’s mental health. Participants were 22–41 years of age, pregnant or up to 6 months postpartum and had an anxiety disorder with or without comorbid depression. Results: Compared to waitlist, participants in cognitive behavioral group therapy reported significantly greater reductions in the primary outcome of anxiety (State-Trait Inventory of Cognitive and Somatic Anxiety, η 2 p = .19; Hamilton Anxiety Rating Scale, η 2 p = .16), as well as in secondary outcomes including worry (Penn State Worry Questionnaire, η 2 p = .29), perceived stress (Perceived Stress Scale, η 2 p = .33) and depressive symptoms (Edinburgh Postnatal Depression Scale, η 2 p = .27; Montgomery–Åsberg Depression Rating Scale, η 2 p = .11). Maternal status (pregnant, postpartum) and medication use were unrelated to treatment outcomes. All gains were maintained, or continued to improve, at 3-month follow-up. Conclusion: Cognitive behavioral group therapy was effective in improving anxiety and related symptoms among women with anxiety disorders in the perinatal period.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".