Psychological and Pharmacological Treatments of Social Phobia: A Meta-Analysis
Bibliographic record
Abstract
A meta-analysis of psychological and pharmacological treatments for social phobia was conducted to evaluate whether the various treatments differ in their efficacy for treating social phobia, whether they are more effective than wait-list and placebo controls, whether rates of attrition differ, and whether treatment gains are maintained at follow-up. A total of 108 treatment-outcome trials for social phobia met inclusion/exclusion criteria for the meta-analysis. Eleven treatment conditions were compared: wait-list control, pill placebo, benzodiazepines (BDZs), selective serotonin reuptake inhibitors (SSRIs), monoamine oxidase inhibitors, attention placebo, exposure (EXP), cognitive restructuring (CR), EXP plus CR, social skills training, and applied relaxation. The most consistently effective treatments for social phobia were pharmacotherapies. BDZs and SSRIs were equally effective and more effective than control conditions. Dropout rates were similar among all the active treatment conditions. Assessment of the durability of treatment gains for pharmacotherapies was not possible because an insufficient number of drug studies included follow-up data. The treatment gains of psychological therapies, although moderate, continued during the follow-up period. BDZs and SSRIs seem to be effective treatments for social phobia, at least in the short term. Recommendations for future research include assessing the long-term outcome for pharmacotherapies and evaluating the inclusion of a cognitive-behavioral treatment during the drug tapering 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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.040 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".