The Contributions of Emotional Engagement with Trauma Material to Outcome in Two Versions of Emotion Focused Trauma Therapy (EFTT)
Bibliographic record
Abstract
The present study had two objectives. The first was to examine the contributions of emotional engagement with trauma material to outcome in two versions of EFTT, each employing a different reexperiencing procedure. These procedures are the IC and empathic exploration (EE) of trauma memories with the therapist. The second objective was to investigate the relative predictive validity of different measurement perspectives of emotional engagement to outcome in the two versions of EFTT. Clients were randomly assigned to therapy condition. Alliance quality was measured with client self-reports on the Working Alliance Inventory (WAI; Horvath & Greenberg, 1989). Emotional engagement was measured through observer-ratings of videotaped sessions employing the IC and EE procedure using the Levels of Engagement Scale (LES; Paivio et al., 2001) and client self-reports using the Post Session Questionnaire (PSQ; Paivio, Jarry, Chagigiorgis, Hall, & Ralston, in press). Emotional distress was measured with client self-reported subjective units of distress (SUDS) during IC and EE work. Treatment outcome was measured through 7 self-report questionnaires. In terms of similarities between IC and EE, clients reported moderate levels of engagement, from both observer-rated (LES) and self-reported (PSQ) measurement perspectives, which remained stable over the course of both treatment conditions. Furthermore, client self-reported emotional engagement during IC and EE both contributed to treatment outcome as did alliance quality. Finally, there were no significant associations between complex measures of engagement (LES and PSQ) and simple distress (SUDS) and frequency of participation in IC and EE was not significantly associated with client change. In terms of differences between IC and EE, there was a steady decline in distress (SUDS) during IC from early to late sessions (although not statistically significant), whereas distress peaked during middle therapy sessions containing the EE procedure and then significantly declined. There was an association between observer-ratings (LES) and self-reports (PSQ) of engagement only in the IC. Finally, in the IC condition, alliance quality and self-reported emotional engagement during IC contributed to resolution of abuse issues, only, whereas in the EE condition, alliance quality and clients levels of distress contributed to multiple dimensions of change.
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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 | 0.009 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".