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Record W2142473528 · doi:10.3402/ejpt.v3i0.15470

Trauma reactivation under the influence of propranolol: an examination of clinical predictors

2012· article· en· W2142473528 on OpenAlexaff
Joaquin Poundja, Steven Sanche, Jacques Tremblay, Alain Brunet

Bibliographic record

VenueEuropean journal of psychotraumatology · 2012
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsSt Mary's Hospital CentreUniversité de MontréalMcGill UniversityDouglas Mental Health University Institute
Fundersnot available
KeywordsPropranololClinical psychologyComorbidityPosttraumatic stressPsychologyRandomized controlled trialPsychiatryMedicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: In two recent studies conducted by our group, a treatment combining propranolol with a brief reactivation session subsequently reduced posttraumatic stress disorder (PTSD) symptom severity and diagnosis, as well as reducing psychophysiological responses during trauma-related script-driven imagery. One likely explanation for those results is that memory reconsolidation was blocked by propranolol. OBJECTIVE: We explored the influence of various predictors on treatment outcome (i.e., PTSD severity), and whether the treated individuals improved in other important domains of functioning associated with PTSD. METHOD: Thirty-three patients with longstanding PTSD participated in a 6-week open-label trial consisting of actively recalling one's trauma under the influence of propranolol, once a week. RESULTS: Treated patients reported a better quality of life, less comorbid depressive symptoms, less negative emotions in their daily life and during trauma recollections. Women were also found to improve more than men. Type of trauma (childhood vs. adulthood), time elapsed since trauma, borderline personality traits, depressive symptoms severity, Axis I comorbidity, and age did not influence treatment outcome. CONCLUSION: These results must await publication of a randomized-controlled trial to further delineate effectiveness with this novel treatment approach.

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)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.158
GPT teacher head0.441
Teacher spread0.283 · 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 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

Citations50
Published2012
Admission routes1
Has abstractyes

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