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Therapeutic advances: Paroxetine for the treatment of social anxiety disorder

2000· article· en· W4254288036 on OpenAlexaboutno aff
R. Bruce Lydiard, Julio Bobes

Bibliographic record

VenueDepression and Anxiety · 2000
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsnot available
Fundersnot available
KeywordsParoxetineSocial anxietyPlaceboAnxietyPsychiatryPsychologyClinical trialAnxiety disorderMedicineInternal medicineAntidepressantAlternative medicine

Abstract

fetched live from OpenAlex

Data from early studies of selective serotonin reuptake inhibitors have shown that these agents are effective in the treatment of social anxiety disorder (social phobia). This review highlights the outcomes of three large clinical trials of paroxetine in patients with social anxiety disorder. In two of the studies, patients received a flexible dose of paroxetine (20–50�mg/day) or placebo; the third trial was a fixed-dose study, in which patients received paroxetine 20, 40, or 60 mg/day, or placebo. A total of 861 subjects were randomized to treatment for 12 weeks, in centers across the U.S.A., Canada, Europe, and South Africa. The primary outcome measures were the Clinical Global Impressions (CGI) Global Improvement item and Liebowitz Social Anxiety Scale (LSAS) Total Score. In each of the studies, 45–66% of patients receiving paroxetine were rated as responders (very much or much improved on the CGI scale). Paroxetine treatment improved symptoms of social anxiety, as measured by the LSAS, compared with placebo. Differences between paroxetine and placebo groups were statistically significant and were clinically relevant within each study. In general, paroxetine was well tolerated. Paroxetine is effective for the treatment of social anxiety disorder. Based on the findings from these studies, a starting dose of 20 mg/day is recommended. The range of efficacy appears to be 20–50 mg/day for most patients. Depression and Anxiety 11:99–104, 2000. © 2000 Wiley-Liss, Inc.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.907
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.024
GPT teacher head0.341
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2000
Admission routes1
Has abstractyes

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