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Social phobia treated as a problem in social functioning: a controlled comparison of two behavioural group approaches

2000· article· en· W1987044173 on OpenAlexaff
Nira Arbel, Jocelyne Bounader, G. Gaudette, Lise Lachance, François Borgeat, José Fabián, Yves Lamontagne, Paul Sidoun, C. Todorov

Bibliographic record

VenueActa Psychiatrica Scandinavica · 2000
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsSocial anxietySocial skillsPsychologySocial functioningPsychopathologyPhobic disorderAnxietyInterpersonal relationshipInterpersonal communicationPhobiasClinical psychologyWaiting listShynessPsychiatryMedicineSocial psychologySurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: Treatments for social phobia result typically in significant anxiety and avoidance reduction; the repercussions in terms of social functioning, however, are not clear. This controlled study compared two approaches designed to improve the social functioning of social phobics. METHOD: Sixty-eight socially phobic patients were randomly assigned to two treatments focused on improving interpersonal relationships either with or without social skills training or a waiting list; 60 completed treatment and 59 a 1-year follow-up. Treatment was administered in small groups, 14 sessions altogether. RESULTS: No clinically meaningful change was observed during the waiting period. A statistically significant and equivalent improvement obtained in both treatment conditions. CONCLUSION: Both treatments resulted in reduced anxiety, avoidance, general psychopathology and better social functioning that maintained over follow-up. Continuing improvement in remission rates was noted; fully 60% of the patients no longer fulfilled criteria for social phobia at the end of 1-year follow-up.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.077
GPT teacher head0.370
Teacher spread0.293 · 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 designObservational
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

Citations35
Published2000
Admission routes1
Has abstractyes

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