Depth of experiencing and therapeutic alliance: What predicts outcome for whom in emotion‐focused therapy for trauma?
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to determine the extent to which therapeutic processes - working alliance and depth of experiencing - contributed to outcome. METHOD: Individual differences in these processes were examined at the early and working phases to determine their impact on symptom reduction. An archival data set of N = 42 individuals who underwent emotion-focused therapy for trauma for childhood maltreatment was used to examine the differential quality of client processes throughout treatment. RESULTS: For those who had difficulty forming an alliance early in therapy, alliance scores during the working phase were the best predictor of outcome (β = -.42). This was complemented by a process change of improvement in alliance from the early to working phases (d = 1.0). In contrast, for those who had difficulty engaging in deepened experiencing early in therapy, depth of experiencing in the working phase was the best predictor of outcome (β = -.36). This was complemented by an improvement in depth of experiencing from the early to working phases (d = .69). CONCLUSIONS: The findings of this study suggest that focusing on the process that clients have trouble with early in therapy contributes to the best treatment outcome. PRACTITIONER POINTS: Sometimes early treatment sessions reveal an abundance of one kind of processing but limitations to another, which poses a puzzle for treatment planning. Our findings suggest that within the first four sessions, therapists could develop tailored treatments based on the relative presence or absence of critical therapeutic changes processes. When it becomes evident that therapy is progressing with a weaker alliance between client and therapist, therapists should redouble their efforts in alliance-building. However, when therapy is developing in a fashion that lacks deep emotional experiencing on the part of the client, treatment efforts should aim to facilitate a richer exploration of moment-by-moment experience. As such, our findings suggest relying on the existing processing strengths within a dyad (e.g., emphasis on an already strong relationships, or augmenting an existing aptitude for deeper experiencing) while shortcomings exist in another kind of process is not optimal responding. Therapists should focus their work on the process that clients have trouble with early in therapy to facilitate the best treatment outcome.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".