Momentary assessment of interpersonal process in psychotherapy.
Bibliographic record
Abstract
To demonstrate how a novel computer joystick coding method can illuminate the study of interpersonal processes in psychotherapy sessions, we applied it to Shostrom's (1966) well-known films in which a client, Gloria, had sessions with 3 prominent psychotherapists. The joystick method, which records interpersonal behavior as nearly continuous flows on the plane defined by the interpersonal dimensions of control and affiliation, provides an excellent sampling of variability in each person's interpersonal behavior across the session. More important, it yields extensive information about the temporal dynamics that interrelate clients' and therapists' behaviors. Gloria's 3 psychotherapy sessions were characterized using time-series statistical indices and graphical representations. Results demonstrated that patterns of within-person variability tended to be markedly asymmetric, with a predominant, set-point-like interpersonal style from which deviations mostly occurred in just 1 direction (e.g., occasional submissive departures from a modal dominant style). In addition, across each session, the therapist and client showed strongly cyclical variations in both control and affiliation, and these oscillations were entrained to different extents depending on the therapist. We interpreted different patterns of moment-to-moment complementarity of interpersonal behavior in terms of different therapeutic goals, such as fostering a positive alliance versus disconfirming the client's interpersonal expectations. We also showed how this method can be used to provide a more detailed analysis of specific shorter segments from each of the sessions. Finally, we compared our approach to alternative techniques, such as act-to-act lagged relations and dynamic systems and pointed to a variety of possible research and training applications. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".