Integrating motivational interviewing with cognitive-behavioral therapy for severe generalized anxiety disorder: An allegiance-controlled randomized clinical trial.
Bibliographic record
Abstract
OBJECTIVE: Although integrating motivational interviewing (MI) and cognitive-behavioral therapy (CBT) has been recommended for treating anxiety, few well-controlled tests of such integration exist. METHOD: In the present randomized trial for severe generalized anxiety disorder (GAD), we compared the efficacy of 15 sessions of CBT alone (N = 43) versus 4 MI sessions followed by 11 CBT sessions integrated with MI to address client resistance/ambivalence (N = 42). Clients were adults, predominantly female and Caucasian, with a high rate of diagnostic comorbidity. To control for allegiance, therapists were nested within treatment group and supervised separately by experts in the respective treatments. RESULTS: Piecewise multilevel models revealed no between-groups differences in outcomes from pre- to posttreatment; however, there were treatment effects over the follow-up period with MI-CBT clients demonstrating a steeper rate of worry decline (γ = -0.13, p = .03) and general distress reduction (γ = -0.12, p = .01) than CBT alone clients. Also, the odds of no longer meeting GAD diagnostic criteria were ∼5 times higher at 12-months for clients receiving MI-CBT compared with CBT alone. There were also twice as many dropouts in CBT alone compared with MI-CBT (23% vs. 10%); a difference that approached significance (p = .09). The treatments were competently delivered, and intraclass correlations revealed negligible between-therapist effects on the outcomes. CONCLUSIONS: The findings support the integration of MI with CBT for severe GAD and point to the importance of training therapists in appropriate responsivity to in-session markers of resistance and ambivalence. (PsycINFO Database Record
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".