The role of alexithymia in trauma therapy outcomes: Examining improvements in PTSD, dissociation, and interpersonal problems.
Bibliographic record
Abstract
OBJECTIVE: Alexithymia is a personality trait that reflects deficits in the cognitive processing and regulation of emotions (Taylor & Bagby, 2013). It has been closely linked to childhood trauma and reported by individuals presenting with other trauma-related conditions, such as posttraumatic stress disorder (PTSD), dissociation, and interpersonal problems (Powers, Etkin, Gyurak, Bradley, & Jovanovic, 2015). Addressing the emotional deficits associated with alexithymia is fundamental to resolving issues of childhood trauma and, therefore, is at the core of many trauma therapy models (e.g., Cloitre, Koenen, Cohen, & Han, 2002). The current study aims to build upon this foundation by examining the role of alexithymia in the improvements of trauma-specific difficulties prior to and following trauma therapy among treatment-seeking women with histories of childhood abuse. METHOD: Data were collected from 167 participants attending Women Recovering from Abuse Program (WRAP), an 8-week, Stage I, day treatment program using primarily group therapy for women with histories of severe childhood trauma. Participants' level of alexithymia, PTSD, and dissociative symptoms, and interpersonal difficulties were assessed at three time points. RESULTS: Significant positive relationships were found between improvements in alexithymia and improvements on all trauma-specific outcomes over the course of treatment (e.g., baseline to posttreatment) and between distinct stages of WRAP. CONCLUSIONS: These findings underscore the role of alexithymia in trauma therapy, and the need to properly attend to the deficits and issues related to alexithymia at initial stages of therapy with survivors of childhood abuse in order to facilitate improvements in trauma-specific symptoms. (PsycINFO Database Record (c) 2020 APA, all rights reserved).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".