Responsive management of early resistance in cognitive–behavioral therapy for generalized anxiety disorder.
Bibliographic record
Abstract
OBJECTIVE: Client resistance limits the efficacy of cognitive-behavioral therapy (CBT), rendering it an important process marker for clinicians. Yet, little is known about how CBT therapists' responsively navigate resistance. This study examined whether differences in therapists' behavior during moments of early resistance in CBT predict distal (posttreatment worry) and proximal (subsequent resistance) therapy outcomes. We hypothesized that clinicians' use of supportive, motivational interviewing (MI)-consistent strategies versus directive CBT methods during resistance episodes would relate to more favorable outcomes. METHOD: Clients (N = 30) with severe generalized anxiety disorder (GAD) were treated with CBT (without MI) in the context of a randomized controlled trial. An adapted version of the Client Resistance Code was used to identify moments of client disagreement with therapist direction, and these episodes were rated for therapist behavior using the Motivational Interviewing Treatment Integrity (MITI). Context-specific variations in therapists' MITI ratings during disagreement were compared with variations in ratings during randomly selected moments to examine whether the timing of therapist use of theoretically indicated MI skills differentially impacted outcomes. RESULTS: Clients whose therapists displayed greater MI-consistent responses during disagreement had lower levels of posttreatment worry, t = -2.84, p = .009, and subsequent resistance, t = -2.96, p = .013. Additionally, MI-consistent behavior during disagreement was substantially related to treatment outcomes, but MI-like behavior during randomly selected therapy segments was not (t = -.15, p = .886 for posttreatment worry, and t = -.09, p = .934 for subsequent resistance). CONCLUSIONS: Findings support the importance of context-responsivity to resistance markers, suggesting that systematic incorporation of MI for managing resistance holds promise for improving CBT for GAD. (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 | 0.001 | 0.005 |
| 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) | 0.001 | 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".