Predictors of Response in Generalized Social Phobia
Bibliographic record
Abstract
Selective serotonin reuptake inhibitors (SSRIs) are the gold standard for the pharmacological treatment of generalized social phobia (GSP). However, little is known about the predictors of response to treatment. Two hundred and four outpatients with GSP were randomized to sertraline (Zoloft) or placebo, for a 20-week double-blind study, with a flexible dose range of sertraline 50 to 200 mg/d. Response was defined as the percentage of patients with a Clinical Global Impression-Improvement scale (CGI-I) of 1 (very much improved) or 2 (much improved). Outcome analyses were conducted using regression models including treatment group as a categorical predictor and study visit as a repeated measure. Dependent measures included Marks Fear Questionnaire (MFQ), Brief Social Phobia Scale (BSPS), CGI-I, and Sheehan Disability Scale (SDS). We investigated several possible predictors of response to treatment including DSM-IV comorbidity, age, sex, age of onset of GSP, and duration of illness. Patients with later-onset (especially adult-onset) GSP tend to have a better response to treatment than those with earlier-onset GSP. This result generally appears in our analyses as a 2-way interaction, where the association with response is greatest for patients with adult-onset GSP (in contrast to those with child or adolescent onset). This finding is most robust for symptom measures, but is still apparent for the Sheehan measure of disability at work. This advantage for later-onset GSP can be accounted for neither by severity of illness nor by duration of illness. Superior treatment outcome for later-onset GSP may be mediated by the degree of social and family disability.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".