An examination of the relationships among clients' affect regulation, in-session emotional processing, the working alliance, and outcome
Bibliographic record
Abstract
The objectives were to examine the relationships among clients' affect regulation capacities, in-session emotional processing, outcome, and the working alliance in 66 clients who received either cognitive-behavioral therapy or process-experiential emotion-focused therapy for depression. Clients' initial level of affect regulation predicted their level of emotional processing during early and working phases of therapy. Clients' peak emotional processing in the working phase of therapy mediated the relationship between their initial level of affect regulation and their level of affect regulation at the end of therapy; and clients' level of affect regulation at the end of therapy mediated the relationship between their peak level of emotional processing in the working phase of therapy and outcome. Clients' affect regulation at the end of therapy predicted outcome independently of the working alliance. The findings suggest that clients' level of affect regulation early in therapy has a significant impact on the quality of their in-session processing and outcome in short-term therapy. Limitations of the study and future directions for research are discussed.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".