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Record W2335081679 · doi:10.1017/bec.2013.32

Effect of Comorbid Depression on Cognitive Behavioural Group Therapy for Social Anxiety Disorder

2014· article· en· W2335081679 on OpenAlexaff
Joelle LeMoult, Karen Rowa, Martin M. Antony, Susan Chudzik, Randi E. McCabe

Bibliographic record

VenueBehaviour Change · 2014
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsToronto Metropolitan UniversityMcMaster UniversitySt. Joseph’s Healthcare Hamilton
Fundersnot available
KeywordsSocial anxietyAnxietyDepression (economics)PsychologyClinical psychologyPsychiatryGroup psychotherapyDepressive symptomsCognitionCognitive behavioral therapy

Abstract

fetched live from OpenAlex

Abstract Many individuals seeking treatment for social anxiety disorder (SAD) also meet criteria for a comorbid depressive disorder. Little is known, however, about how a comorbid depressive disorder affects social anxiety treatment. This study examined 61 participants with SAD and 72 with SAD and a comorbid depressive disorder (SAD+D) before and after 12 weeks of cognitive behavioural group therapy (CBGT) for social anxiety. Although patients with SAD+D reported more severe symptoms of social anxiety and depression at pretreatment, treatment was similarly effective for individuals with SAD and SAD+D. However, individuals with SAD+D continued to report higher symptom severity at post-treatment. Interestingly, CBGT for social anxiety also led to improvements in depressive symptoms despite the fact that depression was not targeted during treatment. Improvement in social anxiety symptoms predicted 26.8% of the variance in improvement in depressive symptoms. Results suggest that depressive symptoms need not be in remission for individuals to benefit from CBGT for social anxiety. However, more than 12 sessions of CBGT may be beneficial for individuals with comorbid depression.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.075
GPT teacher head0.385
Teacher spread0.310 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2014
Admission routes1
Has abstractyes

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