MétaCan
Menu
Back to cohort
Record W2073561954 · doi:10.3402/ejpt.v4i0.21572

Randomized controlled trial of a brief dyadic cognitive-behavioral intervention designed to prevent PTSD

2013· article· en· W2073561954 on OpenAlexaff
Alain Brunet, Isabeau Bousquet Des Groseilliers, Matthew J. Cordova, Josef I. Ruzek

Bibliographic record

VenueEuropean journal of psychotraumatology · 2013
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversité du Québec à MontréalMcGill UniversityDouglas College
Fundersnot available
KeywordsIntervention (counseling)Randomized controlled trialPsychological interventionClinical psychologyCognitionPsychologyMedicineCognitive behavioral therapyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: There is a dearth of effective interventions to prevent the development of post-traumatic stress disorder (PTSD). METHOD: We evaluated the efficacy of a brief dyadic two-session cognitive-behavioral intervention through a controlled trial involving trauma-exposed individuals recruited at the hospital's emergency room. Participants were randomly assigned to either the dyadic intervention group (n=37) or to a waiting list (assessment only) group (n=37). RESULTS: In an intent-to-treat analysis, a time-by-group interaction was found, whereby the treated participants had less PTSD symptoms at the post-treatment but not at the pre-treatment compared to controls. Controlling for the improvement observed in the control participants, the intervention yielded a net effect size of d=0.39. CONCLUSIONS: A brief, early, and effective intervention can be provided by nurses or social workers in hospital settings, at a fairly low cost to individuals presenting to the emergency room as the result of trauma exposure.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0130.001

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.

Opus teacher head0.083
GPT teacher head0.413
Teacher spread0.330 · 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 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

Citations40
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueEuropean journal of psychotraumatologySame topicPosttraumatic Stress Disorder ResearchFrench-language works237,207