Change Processes in Clients' Self-Perceptions in Experiental Psychotherapy / Veränderungsprozesse in der Selbstwahrnehmung bei Klienten in der Experienziellen Psychotherapie / Procesos de cambio en la percepción que tiene el cliente de su self en psicoterapia experiencial / Les processus de changement dans les perceptions de soi chez les clients dans la psychothérapie expérientielle / Processos de mudança na auto-percepção do cliente em terapia experiencial /
Bibliographic record
Abstract
This study examined the processes underlying change in self-perceptions and their relation to treatment outcome in short-term perception-focused experiential therapy. Clients (n = 20) receiving this method of therapy showed significantly greater improvement on measures of depression, self-concept, and perceptual congruence than those in a stress-management treatment control group (n = 20). Self-relevant segments, drawn from an early and later therapy session of the treatment group, were rated on the EXP-Scale and on a measure of levels of perceptual processing (LCPP-R). The analyses revealed significant early- to late-therapy improvement in depth of experiencing and ability to engage in complex, internally focused differentiating, reevaluating, and integrating kinds of mental operations. A significant relationship was also found between attained complexity in manner of processing and post-treatment reduction in depression. The implications of these findings for experiential theory and practice 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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".