Does the Form or the Amount of Exposure Make a Difference in the Cognitive-Behavioral Therapy Treatment of Social Phobia?
Bibliographic record
Abstract
Exposure is considered to be an essential ingredient of cognitive-behavioral therapy treatment of social phobia and of most anxiety disorders. To assess the impact of the amount of exposure on outcome, 30 social phobic patients were randomly allocated to 1 of 2 group treatments of 8 weekly sessions: Self-Focused Exposure Therapy which is based essentially on prolonged exposure to public speaking combined with positive feedback or a more standard cognitive and behavioral method encompassing psychoeducation, cognitive work, working through exposure hierarchies of feared situations for exposure within and outside the group. The results show that the 2 methods led to significant and equivalent symptomatic improvements which were maintained at 1-year follow-up. There was a more rapid and initially more pronounced decrease in negative cognitions with the Self-Focused Exposure Therapy, which included no formal cognitive work, than with the more standard approach in which approximately a third of the content was cognitive. In contrast, decrease in social avoidance was more persistent with standard cognitive-behavior therapy which involved less exposure. The results indicate that positive cognitive change can be achieved more rapidly with non cognitive methods while avoidance decreases more reliably with a standard approach rather than an approach with an exclusive focus on exposure.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".