Responding to <i>In-the-Moment</i> Distress in Emotion-Focused Therapy
Bibliographic record
Abstract
Emotion-focused therapy offers a setting in which clients report on their personal experiences, some of which involve intense moments of distress. This article examines video-recorded interactional sequences of client distress displays and therapist responses. Two main findings extend understanding of embodied actions clients display as both a collection of distress features and as interactional resources therapists draw upon to facilitate therapeutic intervention. First, clients drew from a number of vocal and nonvocal resources that tend to cluster on a continuum of lower or higher intensities of upset displays. Second, we identified three therapist response types that oriented explicitly to clients’ in-the-moment distress: noticings, emotional immediacy questions, and modulating directives. The first two action types draw attention to or topicalize the client’s emotional display; the third type, by contrast, had a regulatory function, either sustaining or abating the intensity of the upset. Data are in North American English.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".