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Record W2795298010 · doi:10.5772/intechopen.70899

Imagery Rehearsal Therapy (IRT) Combined with Cognitive Behavioral Therapy (CBT)

2018· book-chapter· en· W2795298010 on OpenAlexaff
Katia Levrier, André Marchand, Valérie Billette, Stéphane Guay, Geneviève Belleville

Bibliographic record

VenueInTech eBooks · 2018
Typebook-chapter
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversité LavalInstitut Universitaire en Santé Mentale de QuébecInstitut du Savoir MontfortUniversité du Québec à Montréal
Fundersnot available
KeywordsPsychologyClinical psychologyDistressCognitive behavioral therapyCognitionCognitive processing therapyPsychotherapistPsychiatry

Abstract

fetched live from OpenAlex

In cases of post-traumatic stress disorder (PTSD), nightmares can often persist, even after a cognitive behavioral therapy (CBT) for this disorder. Imagery rehearsal therapy (IRT) is a CBT that targets the treatment of nightmares directly. Objectives: the present study describes the feasibility and the efficacy of combining IRT with first-line, trauma-focused CBT for PTSD. Method: two individuals with PTSD took part in this experimental case study protocol. The efficacy of the combined treatment was evaluated using semi-structured interviews, self-report questionnaires, and daily self-monitoring diaries. Results: after three IRT sessions for Participant 1 and five IRT sessions for Participant 2, combined with CBT for PTSD, both participants experienced a slight decrease in sleep difficulties and in the intensity of their PTSD symptoms post-treatment. More particularly, one participant demonstrated a significant decrease in the level of distress associated with his post-traumatic nightmares (PTNM). Conclusions: these results demonstrate that it is possible and promising to combine IRT with CBT for PTSD.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.850
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0200.003

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 head0.127
GPT teacher head0.396
Teacher spread0.269 · 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; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreOther

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

Citations4
Published2018
Admission routes1
Has abstractyes

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