Ambivalence and the working alliance in variants of cognitive‐behavioural therapy for generalised anxiety disorder
Bibliographic record
Abstract
Abstract Client characteristics are widely understood to influence alliance development. However, few studies have examined the role of client ambivalence about therapeutic change. Building on past research demonstrating associations between ambivalence and therapy relationship variables, such as resistance, this study examined whether greater ambivalence was associated with poorer alliance quality. Further, it examined whether motivational interviewing (MI), which involves strategies for managing ambivalence, moderated this relationship. Using data from a randomised controlled trial of cognitive‐behavioural therapy (CBT) for 71 individuals who completed treatment for generalised anxiety disorder, this study tested whether ambivalence, operationalised as observed motivational language against change (counter‐change talk; CCT), in session 1 was related to client‐rated alliance quality over time, and whether this relationship varied between two treatments: MI integrated with CBT (MI‐CBT) or CBT alone. CCT predicted lower client alliance ratings at the early, middle and late stages of therapy. At the late stage, treatment group was a significant moderator, such that CCT was associated with poorer alliances for CBT alone, but not for MI‐CBT. Results suggest that early ambivalence can predict early and middle phase alliance problems in both treatments and that, without explicit strategies for managing ambivalence, early CCT is strongly associated with poorer alliances during the late stage of CBT treatment. This research highlights the importance for clinician responsivity to early motivational markers.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".