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Record W2602963023 · doi:10.1037/cfp0000071

Present- and trauma-focused cognitive–behavioral conjoint therapy for posttraumatic stress disorder: A case study.

2017· article· en· W2602963023 on OpenAlexaff
Nicole D. Pukay‐Martin, Lindsey Torbit, Meredith S. H. Landy, Alexandra Macdonald, Candice M. Monson

Bibliographic record

VenueCouple and Family Psychology Research and Practice · 2017
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCognitive processing therapyClinical psychologyCognitionPsychologyDistressPosttraumatic stressCognitive therapyCognitive behavioral therapyPsychotherapistPsychiatry

Abstract

fetched live from OpenAlex

The bidirectional association between posttraumatic stress disorder (PTSD) and intimate relationship functioning has been well established, and conjoint therapies for PTSD have been created to simultaneously improve PTSD and relationship distress. However, some couples are unwilling to participate in trauma-focused therapy; therefore, a present-focused version of cognitive–behavioral conjoint therapy for PTSD (pf-CBCT for PTSD) was created to decrease barriers to treatment. We propose that, along with trauma-focused cognitive–behavioral conjoint therapy for PTSD (CBCT for PTSD), pf-CBCT for PTSD can be used as part of a sequential approach to PTSD treatment. The various phases of pf-CBCT for PTSD and CBCT for PTSD may be flexibly delivered according to a particular couple’s unique needs and preferences. We present a case study to illustrate this approach of using both pf-CBCT for PTSD and CBCT for PTSD with trauma-focused sessions. The case study describes conjoint treatment of a woman with PTSD related to childhood sexual abuse and her cohabiting partner of 25 years. Discussion provides additional clinical considerations and directions for future research.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.814
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.341
GPT teacher head0.536
Teacher spread0.195 · 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

Citations3
Published2017
Admission routes1
Has abstractyes

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