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Record W1587458175 · doi:10.1177/070674371005500311

Social Support Moderates Outcome in a Randomized Controlled Trial of Exposure Therapy and (or) Cognitive Restructuring for Chronic Posttraumatic Stress Disorder

2010· article· en· W1587458175 on OpenAlexvenueno aff
Sian Thrasher, Mick Power, Nicola Morant, Isaac Marks, Tim Dalgleish

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2010
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsnot available
FundersWellcome Trust
KeywordsCognitive restructuringRandomized controlled trialCognitive therapyPsychologyClinical psychologySocial supportPsychological interventionExposure therapyCognitive behavioral therapyCognitionCognitive processing therapyPsychiatryPsychotherapistMedicineAnxietyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To understand what predicts good outcome in psychiatric treatments, thus creating a pathway to improving efficacy. METHOD: Our study investigated relations between predictor variables and outcome (on the Clinician Administered Posttraumatic Stress Disorder [PTSD] Scale [CAPS]) at posttreatment for 77 treatment completers in a randomized controlled trial of exposure therapy and (or) cognitive restructuring, compared with relaxation, for chronic PTSD in adults. RESULTS: More social support on the Significant Others Scale significantly predicted better outcome on the CAPS, even after controlling for the effects of treatment group and of pretreatment severity. Importantly, social support was only a significant predictor of outcome for participants receiving cognitive restructuring and (or) exposure therapy and not for participants in the relaxation condition. CONCLUSIONS: Better social support is associated with significantly greater gain following cognitive restructuring and (or) exposure therapy for PTSD. Future interventions should consider augmenting social support as an adjunct to treatment.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.375
Teacher spread0.320 · 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.

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

Citations68
Published2010
Admission routes1
Has abstractyes

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