Korean Guidelines for the Pharmacological Treatment of Social Anxiety Disorder: Initial Treatment Strategies
Bibliographic record
Abstract
OBJECTIVE: The aim of the present study was to provide clinical consensus and evidence regarding initial treatment strategies for the pharmacological treatment of social anxiety disorder (SAD) in Korea. METHODS: We prepared a questionnaire to derive a consensus from clinicians regarding their preference for the pharmacological treatment of SAD in Korea. Data regarding medication regimens and psychotropic drugs used during initial treatment, the doses used, and the pharmacological treatment duration were obtained. Responses were obtained from 66 SAD experts, and their opinions were classified into three categories (first-line, second-line, third-line) using a chi-square analysis. RESULTS: Clinicians agreed upon first-line regimens for SAD involving monotherapy with selective serotonin reuptake inhibitors (SSRIs) or the serotonin-norepinephrine reuptake inhibitor (SNRI) venlafaxine, or combined therapy using antidepressants with betablockers or benzodiazepines on a standing or as-needed basis. First-line psychotropic drug choices for initial treatment included the following: escitalopram, paroxetine, sertraline, venlafaxine, and propranolol. The medication dosage used by domestic clinicians was found to be comparable with foreign guidelines. Domestic clinicians tended to make treatment decisions in a shorter amount of time and preferred a similar duration of maintenance treatment for SAD when compared with foreign clinicians. CONCLUSION: This study may provide significant information for developing SAD pharmacotherapy guidelines in Korea, especially in the early stage of treatment.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".