Does Change Occur for the Reasons We Think It Does? A Test of Specific Therapeutic Operations During Cognitive-Behavioral Treatment of Chronic Pain
Bibliographic record
Abstract
OBJECTIVE: To examine the relative validity of 2 conceptual models-Specific, General-by which therapeutic mechanisms in cognitive-behavioral therapy (CBT) for chronic pain achieve favorable outcomes. METHODS: As part of a clinical trial of enhanced versus standard CBT, people with chronic pain received treatment consisting of 3 pain coping skill modules. In secondary analyses of a subsample (n=56), we examined pretreatment to session 4 (of 10 sessions) changes in Chronic Pain Coping Inventory subscales that corresponded to receipt of one of 3 modules; namely Relaxation, Exercise, and Cognitive Coping modules. RESULTS: Findings indicated that: (1) participants receiving the Relaxation module improved more than other groups in relaxation skills, and improved substantially on other coping skills, as well; (2) participants receiving Exercise and Cognitive Coping modules showed mixed improvements and did not improve more than other groups on exercise use or cognitive coping, respectively; and (3) measures of patient-therapist working alliance and patient expectations of treatment benefit at session three correlated significantly with some coping skills changes. DISCUSSION: Change with CBT may occur both by theory-specified mechanisms and general mechanisms. However, the results provide the most support for a General Mechanism model in which changes on coping skills have spreading effects on the use of other coping skills. Significant relationships between some skill changes and indexes of patient-therapist working alliance and outcome expectations suggest that nonspecific factors also play a role in treatment-related changes in the use of pain coping strategies.
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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 | 0.012 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".