Congruence of group therapist and group member alliance judgments in emotionally focused group therapy for binge eating disorder.
Bibliographic record
Abstract
We used West and Kenny's (2011) Truth-and-Bias (T&B) model to examine how accurately group therapists' judge their group members' alliances, and the effects of therapist-patient congruence in alliance ratings on patient outcomes. Were considered: (a) directional bias - therapists' tendency to over- or underrate their clients' alliances, (b) truth strength - clients' alliance ratings, and (c) bias strength - therapists' tendency to conflate their alliance ratings for a specific group member with the average alliance ratings for the other members of the group. There were 118 obese adult patients with binge-eating disorder that were treated by 8 therapists with Emotionally Focused Group Therapy. Outcomes were operationalized as pre- to postchanges in: health-related quality of life, binge eating, and psychological distress. Patients' and therapists' working alliance were assessed after the 2nd, 10th, and last (20th) group therapy sessions. (a) There was no significant congruence between group therapists' and members' ratings of alliance; (b) therapists' ratings of an individual group member's alliance were significantly related to therapists' ratings of the other group members' alliance in early sessions but unrelated in later sessions; and (c) the relationship between therapists' alliance ratings and bias strength was weaker when patient binge eating outcomes improved. Group therapists adopted a "better safe than sorry" strategy by underestimating the strength of their group members' alliances. Therapists had a tendency to judge each group member's individual alliance based on the aggregated alliance of the other group members. Improvement in patient binge eating outcomes was related to therapists overcoming this tendency. (PsycINFO Database Record
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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 | 0.023 | 0.105 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".