The Predictive Capacity of Self-Reported Motivation vs. Observed Motivational Language in Cognitive Behavioural Therapy for Generalized Anxiety Disorder
Bibliographic record
Abstract
Client change motivation is considered a key factor in psychotherapy. Existing research on motivation has largely relied on self-report, which is prone to response bias and inconsistently related to treatment outcome. In contrast, early observed client in-session language may be a more valid measure of initial motivation. The present study investigated 85 clients undergoing cognitive behavioural therapy alone (CBT) or CBT infused with motivational interviewing (MI-CBT) for generalized anxiety disorder. The aims were: (1) to compare the predictive capacity of motivational language vs. self-reported motivation, and (2) to examine the influence of treatment condition on motivational language. Findings revealed motivational language explained up to 38% of outcome variance, even 1-year posttreatment. In contrast, self-reported motivation failed to predict outcome. Moreover, MI-CBT was associated with a decrease in detrimental motivational language compared to CBT alone. These findings support attending to motivational language in CBT and responding to these markers using MI.
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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 | 0.008 |
| 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 | 0.000 |
| 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".