Can we improve cognitive–behavioral therapy for chronic back pain treatment engagement and adherence? A controlled trial of tailored versus standard therapy.
Bibliographic record
Abstract
OBJECTIVE: This study evaluated whether tailored cognitive-behavioral therapy (TCBT) that incorporated preferences for learning specific cognitive and/or behavioral skills and used motivational enhancement strategies would improve treatment engagement and participation compared with standard CBT (SCBT). We hypothesized that participants receiving TCBT would show a lower dropout rate, attend more sessions, and report more frequent intersession pain coping skill practice than those receiving SCBT. We also hypothesized that indices of engagement and adherence would correlate with pre- to posttreatment changes in outcome factors. METHOD: One hundred twenty-eight of 161 consenting persons with chronic back pain who completed baseline measures were allocated to either TCBT or SCBT using a modified randomization procedure. Participants completed daily ratings of pain coping skill practice and goal accomplishment during treatment, as well as measures of pain severity, disability, and other key outcomes at the end of treatment. RESULTS: No significant differences between treatment groups were noted on measures of treatment engagement or adherence. However, these factors were significantly related to some pre- to posttreatment improvements in outcomes, regardless of treatment condition. CONCLUSIONS: Participants in this study evidenced a high degree of participation and adherence, but treatment tailored to take into account participant preferences, and that employed motivational enhancement strategies, failed to increase treatment participation over and above SCBT for chronic back pain. Evidence that participation and adherence were associated with positive outcomes supports continued clinical and research efforts focusing on these therapeutic processes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".