Long-Term Effects of Short-Term Psychodynamic Psychotherapy and Cognitive-Behavioural Therapy in Generalized Anxiety Disorder: 12-Month Follow-up
Bibliographic record
Abstract
OBJECTIVE: In a previous randomized controlled trial (RCT), short-term efficacy of cognitive-behavioural therapy (CBT) and short-term psychodynamic psychotherapy (STPP) in generalized anxiety disorder (GAD) was demonstrated. In this article, long-term stability of these effects will be examined. Effects of CBT and STPP will be compared. METHOD: In the original RCT, patients with GAD were treated with either CBT (n = 29) or STPP (n = 28). Treatments were carried out according to manuals and included up to 30 sessions. As the primary outcome measure the Hamilton Anxiety Rating Scale was used. In addition to short-term outcome previously reported, treatment effects were assessed 12 months after termination of treatment. RESULTS: Both CBT and STPP yielded large improvements at 12-month follow-up. No significant differences were found between treatments concerning the primary outcome measure. This result was corroborated by 3 self-report measures of anxiety. However, in measures of trait anxiety and worry, CBT was superior. Concerning depression, differences reported at posttreatment were no longer significant at 12-month follow-up. CONCLUSIONS: In GAD, both CBT and STPP yield large and stable effects 12 months after treatment. Concerning trait anxiety and worry, CBT seems to be superior. For STPP, further studies should be carried out to confirm the results.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".