The Essence of Process-Experiential/Emotion-Focused Therapy
Bibliographic record
Abstract
Process-Experiential/Emotion-Focused Therapy (PE-EFT) is an empirically-supported, neo-humanistic approach that integrates and updates person-centered, Gestalt, and existential therapies. In this article, we first present what we see as PE-EFT's five essential features, namely neo-humanistic values, process-experiential emotion theory, person-centered but process-guiding relational stance, therapist exploratory response style, and marker-guided task strategy. Next, we summarize six treatment principles that guide therapists in carrying out this therapy: achieving empathic attunement, fostering an empathic, caring therapeutic bond, facilitating task collaboration, helping the client process experience appropriately to the task, supporting completion of key client tasks, and fostering client development and empowerment. In general, PE-EFT is an approach that seeks to help clients transform contradictions and impasses into wellsprings for growth.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".