Dynamic emotional processing in experiential therapy: Two steps forward, one step back.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The study of dynamic and nonlinear change has been a valuable development in psychotherapy process research. However, little advancement has been made in describing how moment-by-moment affective processes contribute to larger units of change. The purpose of this study was to examine observable moment-by-moment sequences in emotional processing as they occurred within productive sessions of experiential therapy. This article further tested A. Pascual-Leone and L. S. Greenberg's (2007) model of emotional processing through a reanalysis of their data sample of 34 sessions in which clients presented with global distress: 17 that ended in poor in-session events and 17 that ended in good in-session events. Current analyses used univariate and bootstrapping statistical methods to examine how dynamic temporal patterns in clients' emotion accumulated moment-by-moment to produce in-session gains in emotional processing. Results show that effective emotional processing was simultaneously associated with steady improvement according to the model as well as increased emotional range. Consequentially, good events were shown to occur in a 2-steps-forward, 1-step-back fashion. Finally, good events were also shown to have progressively shortened emotional collapses, whereas the opposite was true for poor in-session events.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it